What are Datasets?

Datasets are defined file collections, whose access is governed by a Data Access Committee (DAC).

Total number of Datasets: 2094
Displaying 1 - 2094

Dataset Accession Description Technology Samples File Types
EGAD00001001856 100 other
EGAD00001000602 Illumina HiSeq 2000; 1 bam
EGAD00001000393 Illumina HiSeq 2000; 30 vcf
EGAD00001000597 Illumina HiSeq 2000; 212 bam
EGAD00001000601 Illumina HiSeq 2000; 1 bam
EGAD00001000427 Illumina HiSeq 2000; 30 bam
EGAD00001000628 Illumina HiSeq 2000;, Illumina Genome Analyzer IIx; 66 bam
EGAD00001000632 AB SOLiD 4 System; 12 SOLiD_native_csfasta,SOLiD_native_qual,bam
EGAD00001000659 Illumina HiSeq 2000; 12 bam
EGAD00001000642 Illumina HiScanSQ; 2 bam
EGAD00001000643 Illumina HiScanSQ; 2 bam
EGAD00001001260 Illumina HiSeq 2000; 2 fastq
EGAD00001000667 Illumina HiSeq 2000; 72 bam
EGAD00001000714 102 bam
EGAD00001000711 Illumina HiSeq 2000; 42 bam
EGAD00001000713 Illumina HiSeq 2000; 12 bam
EGAD00001000712 Illumina HiSeq 2000; 72 bam
EGAD00001000856 Illumina HiSeq 2000; 1 fastq
EGAD00001000749 Illumina HiSeq 2000; 12 bam
EGAD00001000704 Illumina HiSeq 2000; 44 bam
EGAD00001000779 AB SOLiD 4 System; 2 bam
EGAD00001000724 Illumina HiSeq 2000; 68 bam
EGAD00001000830 Illumina HiSeq 2000; 14 bam
EGAD00001000834 Illumina HiSeq 2000; 20 bam
EGAD00001000833 Illumina HiSeq 2000; 10 bam
EGAD00001000832 Illumina HiSeq 2000; 16 bam
EGAD00001000829 Illumina HiSeq 2000; 16 bam
EGAD00001000831 Illumina HiSeq 2000; 30 bam
EGAD00001000835 Illumina HiSeq 2000; 8 bam
EGAD00001000849 Illumina HiSeq 2000; 50 bam
EGAD00001000876 Illumina HiSeq 2000; 98 fastq
EGAD00001000880 233 bam,vcf
EGAD00001001213 Illumina HiSeq 2000; 88 bam
EGAD00001001270 Illumina HiSeq 2000; 196 bam
EGAD00001001258 Illumina HiSeq 2000; 5 fastq
EGAD00001001259 Illumina HiSeq 2000; 2 fastq
EGAD00001001257 Illumina HiSeq 2000; 3 fastq
EGAD00001001115 Illumina HiSeq 2500; 54 fastq
EGAD00001000843 Illumina HiSeq 2000; 12 fastq
EGAD00001000844 Illumina HiSeq 2000; 22 fastq
EGAD00001000836 Illumina HiSeq 2000; 49 bam
EGAD00001000780 Illumina HiSeq 2000; 18 fastq
EGAD00001000759 Illumina HiSeq 2000; 86 bam,fastq
EGAD00001001001 2 bam
EGAD00001000896 Illumina HiSeq 2000; 12 bam
EGAD00001001860 19 vcf
EGAD00001001036 Illumina HiSeq 2000; 26 fastq
EGAD00001001044 Ion Torrent PGM; 2 bam
EGAD00001001043 Illumina HiSeq 2000; 8 bam
EGAD00001001014 Illumina HiSeq 2000; 2,597 bam
EGAD00001001015 Illumina HiSeq 2000; 76 bam
EGAD00001000845 44 bam
EGAD00001001072 Illumina MiSeq; 5 fastq
EGAD00001001329 28 bam
EGAD00001001051 Illumina HiSeq 2000; 200 fastq
EGAD00001001094 Illumina HiSeq 2500; 247 fastq
EGAD00001001095 Illumina HiSeq 2000;, Illumina HiSeq 2500; 508 bam,fastq
EGAD00001001859 Illumina HiSeq 2500; 2 fastq
EGAD00001001858 Illumina HiSeq 2500; 2 fastq
EGAD00001001113 Illumina HiSeq 2000; 46 bam
EGAD00001001060 Illumina HiSeq 2000; 112 bam
EGAD00001001084 Illumina HiSeq 2000; 209 fastq
EGAD00001001083 Illumina HiSeq 2000; 2 fastq
EGAD00001001126 340 other
EGAD00001001218 10 bam
EGAD00001001217 15 bam
EGAD00001001096 Illumina HiSeq 2000; 419 bam
EGAD00001001221 Illumina HiSeq 2500; 54 fastq
EGAD00001001220 Illumina HiSeq 1000; 10 bam
EGAD00001001302 Illumina HiSeq 2500; 2 bam
EGAD00001001391 Illumina HiSeq 2000; 3 bam
EGAD00001001423 Illumina HiSeq 2000; 7 bam
EGAD00001001436 AB 5500 Genetic Analyzer; 4 bam
EGAD00001001443 Illumina Genome Analyzer II; 199 fastq
EGAD00001001272 Illumina HiSeq 2000; 15 fastq
EGAD00001001616 2 bam
EGAD00001001614 26 bam
EGAD00001001613 10 bam
EGAD00001001615 10 bam
EGAD00001001602 Illumina HiSeq 2000; 1 fastq
EGAD00001001628 Illumina MiSeq;, Illumina HiSeq 2500; 142 bam
EGAD00001001631 Illumina MiSeq; 334 fastq
EGAD00001001275 Illumina HiSeq 2000; 1 fastq
EGAD00001001627 Illumina HiSeq 2000; 4 bam
EGAD00001001056 Illumina HiSeq 2000; 7 bam
EGAD00001001688 Illumina HiSeq 2500; 34 fastq
EGAD00001001689 Illumina HiSeq 2500; 27 fastq
EGAD00001001687 Illumina HiSeq 2000; 56 bam,fastq
EGAD00001001068 Illumina HiSeq 2000; 1 bam
EGAD00001001070 Illumina HiSeq 2000; 1 bam
EGAD00001001379 Illumina HiSeq 2000; 29 bam
EGAD00001001674 Illumina MiSeq;, Illumina HiSeq 2500; 299 bam
EGAD00001001857 Illumina HiSeq 2000; 381 fastq
EGAD00001001927 Illumina HiSeq 2000; 27 fastq
EGAD00001001645 Illumina Genome Analyzer II; 28
EGAD00001002191 Illumina HiSeq 2000; 28
EGAD00001001069 Illumina HiSeq 2000; 1
EGAD00001001960 Illumina HiSeq 2000; 171
EGAD00001000840 Illumina HiSeq 2000; 1
EGAD00010000572 Imputation-based meta-analysis of severe malaria in Gambia. 2,870
EGAD00010000570 Imputation-based meta-analysis of severe malaria in Kenya. 3,343
EGAD00001000036 "Copy number variant detection in multiple foci of three prostate cancer tumors" Illumina Genome Analyzer II 9 bam
EGAD00001000035 "Single nucleotide variant detection in multiple foci of three prostate cancer tumors" Illumina Genome Analyzer II 9 bam
EGAD00001000033 "SNV detection from formalin fixed paraffin embedded (FFPE) samples" Illumina Genome Analyzer II 6 bam
EGAD00001000034 "Usage of small amounts of DNA for Illumina sequencing" Illumina Genome Analyzer II 3 bam
EGAD00001001889 ***THIS DATA CAN ONLY BE USED FOR NON-COMMERCIAL CANCER RESEARCH*** Sequencing of organoid cell lines derived from oesophageal tumour sections taken from patients diagnosed with primary oesophageal cancer who underwent tumour resection surgery. HiSeq X Ten; 9 cram
EGAD00001002226 1. Odors are detected, firstly, by olfactory sensory neurons (OSNs) in the olfactory epithelium of the nose. This neurons then project directly to the olfactory bulb in the brain. Olfaction depends on cellular regeneration of the OE, olfactory bulb and hippocampus, and on their continual re-wiring. The olfactory neural pathway includes regions of the frontal, temporal and limbic brain, which in turn overlap with brain areas involved in brain disorders. OSNs are the only aspect of the human brain exposed to the external environment. This not only makes them vulnerable to environmental changes, but also accessible for biomedical studies. We have already sequenced and developed a protocol for analyzing the transcriptome of mouse main olfactory epithelium and single OSNs. We propose here to perform a similar study for samples from the human olfactory epithelium. We have developed a minimally invasive method for obtaining human OSNs, among other cells from the nasal epithelium. In this experiment, we have obtained cell samples from the olfactory epithelium, including OSN, from healthy volunteers. We would like to further characterize them by RNA sequencing. This will give us valuable insight into human olfaction. It will also provide a first step into a new avenue to study, and find biomarkers for, brain diseases though the analysis of these easily available neurons. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ Illumina HiSeq 2500; 8
EGAD00001001456 1000Genomes imputed data set of 581 cases and 417 controls for male-pattern baldness 1 vcf
EGAD00001002204 1006 Familial early onset gemrline CRC patients sequenced by the Molecular and Population Genetics group of the Institute of Cancer Research Illumina HiSeq 2500; 1,006
EGAD00001000618 1204 Sardinian males 1,195 bam
EGAD00001001925 1461 Neuropathological and clinically characterised cases from the MRC Brain Bank 1,461 vcf
EGAD00001001897 15x whole genome sequencing in samples from the Cretan Greek isolate collection HELIC MANOLIS HiSeq X Ten; 1,482 cram
EGAD00010000248 1958BC control samples Illumina ImmunoBeadChip - Illuminus, GenoSNP 6,812
EGAD00010000294 1958BC control samples only (Hap300) 2,436
EGAD00010000296 1958BC control samples only (Hap550) 2,224
EGAD00001001846 2 BRAFV600E cell lines that have been made resistance to 1. the BRAF inhibitor PLX4720 and 2. the combination therapy of dabrafenib and trametinib seem to have a internal duplication in the kinase domain. We would like to know if this is caused by a translocation. HiSeq X Ten; 4 cram
EGAD00001000082 20 Matched Pair Breast Cancer Genomes Illumina HiSeq 2000, Illumina Genome Analyzer II 42 bam
EGAD00001000409 2000 ulcerative colitis cases drawn from the UKIBD Genetics Consortium cohort and whole-genome sequenced at 2X depth. A case control association study using control samples whole-genome sequenced by UK10K will be undertaken to identify common, low-frequency and rare variants associated with ulcerative colitis. Data will be combined with similar data across 3000 Crohn's disease cases from the same cohort to identify inflammatory bowel disease (IBD) loci and better understand the genetic differences and similarities of the two common forms of IBD. Illumina HiSeq 2000; 1,992 bam
EGAD00001000428 204 individuals were genotyped with the Illumina 2.5M Omni chip. Filtered genotypes were imputed into the 1000 genomes project European panel SNPs. Beagle R2 is indicated in VCF files for further filtering. See Materials and Methods in publication for details. 204 vcf
EGAD00010000536 21 unlinked autosomal microsatellite loci for 30 Central Asian populations Applied Biosystems 3100 automated sequencer-GeneMarker v.1.6 (Softgenetics) 1,702
EGAD00010000538 28 unlinked autosomal microsatellite loci for 20 African and 4 philippine populations Applied Biosystems 3100 automated sequencer-GeneMarker v.1.6 (Softgenetics) 1,702
EGAD00010000917 399 tumors profiled using Agilent miRNA microarrays (Product Number G4872A, design ID 046064). The arrays are based on miRBase release 19.0 and 2006 human miRNAs are represented. 150 ng total RNA was used as input. Agilent miRNA microarrays 399
EGAD00010000614 40 Druze Trios 120
EGAD00001001358 463 newly diagnosed patients from the UK Myeloma XI clinical trial (NCT01554852) underwent whole exome sequencing plus targeted capture of the IGH/K/L and MYC loci. 200 ng of DNA were processed using NEBNext DNA library prepartion kit and hybridised to the SureSelect Human All Exon V5 Plus. Four samples were pooled and run on one lane of a HiSeq 2000 using 76-bp paired end reads. DNA from CD138+ selected bone marrow cells (myeloma tumour) as well as peripheral white blood cells were analysed and somatic mutations detected. Illumina HiSeq 2000; 926 bam
EGAD00001001847 4C-seq data was generated for regions of interest to confirm enhancer-gene promoter interactions Illumina HiSeq 2000; 1 fastq
EGAD00001001694 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB10_C 1 other
EGAD00001001695 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB10_F 1 other
EGAD00001001696 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB10_M 1 other
EGAD00001001697 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB15_C 1 other
EGAD00001001698 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB15_F 1 other
EGAD00001001699 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB15_M 1 other
EGAD00001001700 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB1_C 1 other
EGAD00001001701 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB1_F 1 other
EGAD00001001702 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB1_M 1 other
EGAD00001001703 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB21_C 1 other
EGAD00001001704 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB21_F 1 other
EGAD00001001705 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB21_M 1 other
EGAD00001001706 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB22_C 1 other
EGAD00001001707 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB22_F 1 other
EGAD00001001708 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB22_M 1 other
EGAD00001001709 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB23_C 1 other
EGAD00001001710 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB23_F 1 other
EGAD00001001711 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB23_M 1 other
EGAD00001001712 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB24_C 1 other
EGAD00001001713 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB24_F 1 other
EGAD00001001714 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB24_M 1 other
EGAD00001001715 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB25_C 1 other
EGAD00001001716 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB25_F 1 other
EGAD00001001717 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB25_M 1 other
EGAD00001001718 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB27_C 1 other
EGAD00001001719 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB27_F 1 other
EGAD00001001720 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB27_M 1 other
EGAD00001001721 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB28_C 1 other
EGAD00001001722 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB28_F 1 other
EGAD00001001723 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB28_M 1 other
EGAD00001001724 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB30_C 1 other
EGAD00001001725 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB30_F 1 other
EGAD00001001726 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB30_M 1 other
EGAD00001001727 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB31_C 1 other
EGAD00001001728 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB31_F 1 other
EGAD00001001729 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB31_M 1 other
EGAD00001001730 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB33_C 1 other
EGAD00001001731 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB33_F 1 other
EGAD00001001732 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB33_M 1 other
EGAD00001001733 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB35_C 1 other
EGAD00001001734 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB35_F 1 other
EGAD00001001735 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB35_M 1 other
EGAD00001001736 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB38_C 1 other
EGAD00001001737 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB38_F 1 other
EGAD00001001738 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB38_M 1 other
EGAD00001001739 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB40_C 1 other
EGAD00001001740 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB40_F 1 other
EGAD00001001741 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB40_M 1 other
EGAD00001001742 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB41_C 1 other
EGAD00001001743 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB41_F 1 other
EGAD00001001744 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB41_M 1 other
EGAD00001001745 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB42_C 1 other
EGAD00001001746 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB42_F 1 other
EGAD00001001747 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB42_M 1 other
EGAD00001001748 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB43_C 1 other
EGAD00001001749 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB43_F 1 other
EGAD00001001750 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB43_M 1 other
EGAD00001001751 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB44_C 1 other
EGAD00001001752 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB44_F 1 other
EGAD00001001753 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB44_M 1 other
EGAD00001001754 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB4_C 1 other
EGAD00001001755 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB4_F 1 other
EGAD00001001756 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB4_M 1 other
EGAD00001001757 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB50_C 1 other
EGAD00001001758 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB50_F 1 other
EGAD00001001759 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB50_M 1 other
EGAD00001001760 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB51_C 1 other
EGAD00001001761 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB51_F 1 other
EGAD00001001762 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB51_M 1 other
EGAD00001001763 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB52_C 1 other
EGAD00001001764 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB52_F 1 other
EGAD00001001765 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB52_M 1 other
EGAD00001001766 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB55_C 1 other
EGAD00001001767 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB55_F 1 other
EGAD00001001768 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB55_M 1 other
EGAD00001001769 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB57_C 1 other
EGAD00001001770 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB57_F 1 other
EGAD00001001771 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB57_M 1 other
EGAD00001001772 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB58_C 1 other
EGAD00001001773 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB58_F 1 other
EGAD00001001774 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB58_M 1 other
EGAD00001001775 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB60_C 1 other
EGAD00001001776 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB60_F 1 other
EGAD00001001777 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB60_M 1 other
EGAD00001001778 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB62_C 1 other
EGAD00001001779 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB62_F 1 other
EGAD00001001780 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB62_M 1 other
EGAD00001001781 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB8_C 1 other
EGAD00001001782 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB8_F 1 other
EGAD00001001783 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB8_M 1 other
EGAD00001001784 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW12_C 1 other
EGAD00001001785 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW12_F 1 other
EGAD00001001786 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW12_M 1 other
EGAD00001001787 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW14_C 1 other
EGAD00001001788 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW14_F 1 other
EGAD00001001789 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW14_M 1 other
EGAD00001001790 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW15_C 1 other
EGAD00001001791 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW15_F 1 other
EGAD00001001792 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW15_M 1 other
EGAD00001001793 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW18_C 1 other
EGAD00001001794 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW18_F 1 other
EGAD00001001795 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW18_M 1 other
EGAD00001001796 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW20_C 1 other
EGAD00001001797 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW20_F 1 other
EGAD00001001798 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW20_M 1 other
EGAD00001001799 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW22_C 1 other
EGAD00001001800 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW22_F 1 other
EGAD00001001801 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW22_M 1 other
EGAD00001001802 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW24_C 1 other
EGAD00001001803 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW24_F 1 other
EGAD00001001804 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW24_M 1 other
EGAD00001001805 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW27_C 1 other
EGAD00001001806 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW27_F 1 other
EGAD00001001807 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW27_M 1 other
EGAD00001001808 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW29_C 1 other
EGAD00001001809 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW29_F 1 other
EGAD00001001810 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW29_M 1 other
EGAD00001001811 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW2_C 1 other
EGAD00001001812 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW2_F 1 other
EGAD00001001813 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW2_M 1 other
EGAD00001001814 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW32_C 1 other
EGAD00001001815 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW32_F 1 other
EGAD00001001816 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW32_M 1 other
EGAD00001001817 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW38_C 1 other
EGAD00001001818 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW38_F 1 other
EGAD00001001819 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW38_M 1 other
EGAD00001001820 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW3_C 1 other
EGAD00001001821 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW3_F 1 other
EGAD00001001822 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW3_M 1 other
EGAD00001001823 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW46_C 1 other
EGAD00001001824 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW46_F 1 other
EGAD00001001825 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW46_M 1 other
EGAD00001001826 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW47_C 1 other
EGAD00001001827 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW47_F 1 other
EGAD00001001828 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW47_M 1 other
EGAD00001001829 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW49_C 1 other
EGAD00001001830 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW49_F 1 other
EGAD00001001831 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW49_M 1 other
EGAD00001001833 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW4_F 1 other
EGAD00001001834 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW4_M 1 other
EGAD00001001835 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW50_C 1 other
EGAD00001001836 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW50_F 1 other
EGAD00001001837 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW50_M 1 other
EGAD00001001838 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW51_C 1 other
EGAD00001001839 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW51_F 1 other
EGAD00001001840 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW51_M 1 other
EGAD00001001841 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW52_C 1 other
EGAD00001001842 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW52_F 1 other
EGAD00001001843 50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW52_M 1 other
EGAD00010000704 610k genotyping imputed on Hapmap 3 and 1000G Phase 1 CEU 714
EGAD00000000020 685 families where both parents have been genotyped together with the child with severe malaria 0
EGAD00001002111 70 Whole exome sequencing from 9 patients with DIPG for project Spatial and Temporal Homogeneity of Driver Mutations in Diffuse Intrinsic Pointine Glioma Illumina HiSeq 2500; 70
EGAD00000000019 840 families where both parents have been genotyped together with the child with severe malaria 0
EGAD00001000620 A bespoke targeted pulldown experiment will be performed on patients with Angiosarcoma. the resulting products will be sequenced to determine the prevalence of previously found mutations in these patients. Illumina HiSeq 2000; 14 bam
EGAD00001000679 A bespoke targeted pulldown experiment will be performed on patients with Angiosarcoma. the resulting products will be sequenced to determine the prevalence of previously found mutations in these patients. Illumina HiSeq 2000; 107 bam
EGAD00001000948 A comparison of the somatic variation present in a primary colorectal tumour and three different liver metastases from the same patient. Illumina HiSeq 2000; 6 cram
EGAD00001000149 A Comprehensive Catalogue of Somatic Mutations from a Human Cancer Genome Illumina HiSeq 2000 2 srf
EGAD00001001323 A comprehensive characterisation and analysis of human breast cancers through genome-wide approaches through transcriptomics. Illumina HiSeq 2000; 59
EGAD00001001322 A comprehensive characterisation and analysis of human breast cancers through whole-genome sequencing. Illumina HiSeq 2000; 196
EGAD00001000301 A couple of previously characterized and sequenced libraries will be repeated using a couple of differing size selection criteria and skim sequenced using an Illumina HiSeq. The resulting sequence will be analyzed to determine the optimal DNA library size for our specific downstream analysis. Illumina HiSeq 2000; 1 bam
EGAD00001002170 A KNIH004 data set, Whole-Genome Bisulfite Sequencing(WGBS) paired end data, mRNA-Seq paired end data and miRNA-Seq single end data for islet cells Illumina HiSeq 2000;, Illumina HiSeq 2500; 3
EGAD00001002171 A KNIH005 data set, Whole-Genome Bisulfite Sequencing(WGBS) paired end data, mRNA-Seq paired end data and miRNA-Seq single end data for islet cells Illumina HiSeq 2000;, Illumina HiSeq 2500; 3
EGAD00001002173 A KNIH006 data set, Whole-Genome Bisulfite Sequencing(WGBS) paired end data, mRNA-Seq paired end data and miRNA-Seq single end data for adipocytes Illumina HiSeq 2000;, Illumina HiSeq 2500; 3
EGAD00001002172 A KNIH006 data set, Whole-Genome Bisulfite Sequencing(WGBS) paired end data, mRNA-Seq paired end data and miRNA-Seq single end data for βcells Illumina HiSeq 2000;, Illumina HiSeq 2500; 3
EGAD00001002174 A KNIH008 data set, Whole-Genome Bisulfite Sequencing(WGBS) paired end data, mRNA-Seq paired end data and miRNA-Seq single end data for adipocytes Illumina HiSeq 2000;, Illumina HiSeq 2500; 3
EGAD00001002175 A KNIH009 data set, Whole-Genome Bisulfite Sequencing(WGBS) paired end data, mRNA-Seq paired end data and miRNA-Seq single end data for preadipocytes Illumina HiSeq 2000;, Illumina HiSeq 2500; 3
EGAD00001002176 A KNIH010 data set, Whole-Genome Bisulfite Sequencing(WGBS) paired end data, mRNA-Seq paired end data and miRNA-Seq single end data for podocytes Illumina HiSeq 2000;, Illumina HiSeq 2500; 3
EGAD00001002177 A KNIH011 data set, Whole-Genome Bisulfite Sequencing(WGBS) paired end data, mRNA-Seq paired end data and miRNA-Seq single end data for podocytes Illumina HiSeq 2000;, Illumina HiSeq 2500; 3
EGAD00010000626 A new beta-globin mutation responsible of a beta-thalassemia (HbVar database ID 2928) was observed in 8 unrelated French families. The mutation carriers originated from Nord-Pas-de-Calais, a Northern French region where the chief town is Lille. 5 unrelated mutation carriers were genotyped for a set of 12 microsatellites from chromosome 11, around the beta-globin gene. Among the 5 mutation carriers, 4 were genotyped for 97 European Ancestry Informative SNPs (EAIMs). 37
EGAD00010000624 A new beta-globin mutation responsible of a beta-thalassemia (HbVar database ID 2928) was observed in 8 unrelated French families. The mutation carriers originated from Nord-Pas-de-Calais, a Northern French region where the chief town is Lille. 5 unrelated mutation carriers were genotyped for a set of 12 microsatellites from chromosome 11, around the beta-globin gene. Among the 5 mutation carriers, 4 were genotyped for 97 European Ancestry Informative SNPs (EAIMs). 0
EGAD00001001879 A pilot to establish the feasability of using a custom Agilent targeted pulldown of 110 genes implicated in colorectal tumourigensis to sequence for driver mutations in a set of 30 FFPE colorectal adenomas. If successful, we propose to sequence an additional 350 adenomas as part of a MRC research study in order to define the pattern of driver mutations across the spectrum of pathological subtypes including coventional adenomas, serrated adenomas and hyperplastic polyps Illumina HiSeq 2000; 30 cram
EGAD00001000670 A potential and very serious side effect of treating IBD with antiTNFa therapies (the current gold standard) is the development of systemic lupus erythematosis (SLE). This side effect is rare and unpredictable. Out of several thousand cases having received treatment, the University of Calgary have accumulated 12 individuals with full phenotyping and novel serological antibody discovery panel data. We propose to exome sequence these samples in an effort to identify rare highly-penetrant variants that could be underlying this severe phenotype. Illumina HiSeq 2000; 15 bam
EGAD00001000646 A selection of human cancers harbours somatic driver mutations in genes encoding histones, most notably childhood brain tumours with K27M substitutions of the histone 3.3 gene, H3F3A. We performed whole genome sequencing of the benign cartilage tumour, chondroblastoma, and targeted sequencing of histone 3.3 genes, H3F3A and H3F3B, in seven further skeletal tumour types. We identified an exceptionally high prevalence of novel histone 3.3 driver mutations at glycine 34 and at lysine 36. Histone 3.3 gene mutations were found in 91% in giant cell tumours of bone (48/53), mainly H3F3A G34W variants, and in 92% of chondroblastoma (73/79), predominantly K36M mutations in H3F3B. H3F3B is paralogous to the cancer gene H3F3A. However, H3F3B driver variants have not previously been reported in human cancer. Our observation demonstrate remarkable tumour-specificity of mutations, with respect to which histone 3.3 gene and residue is mutated, indicating that the advantage these mutations confer is tumour dependent. Moreover, tumour-specific mutation of H3F3A and H3F3B suggests, that although both genes encode identical proteins, they are likely non-redundant and employed differentially during skeletal development. Illumina HiSeq 2000; 14 bam
EGAD00001001037 A total of 395 couples were subjected to IVF-PGD treatment, including 129 couples with NGS-based test and 266 couples with SNP array based test for the detection of embryonic chromosomal abnormalities. The NGS test was performed using low coverage whole genome sequencing with HiSeq 2000 platform. And the SNP array test was using Affymetrix Gene Chip Mapping Nsp I 262K. The average age of patients was 32.1 years (age range 20-44 years). Illumina HiSeq 2000; 188 fastq
EGAD00010000736 AAD case and control samples from UK and Norway 117
EGAD00010000858 Achalasia cases & controls 8,151
EGAD00001000061 Acral melanoma study whole exomes Illumina Genome Analyzer IIx 3 fastq
EGAD00001000060 Acral melanoma study whole genomes Complete Genomics 3 CompleteGenomics_native
EGAD00001000089 Acute Lymphoblastic Leukemia Exome sequencing Illumina Genome Analyzer II 20 bam
EGAD00001000104 Acute Lymphoblastic Leukemia Exome sequencing 2 Illumina Genome Analyzer II 97 bam
EGAD00001000116 Acute Lymphoblastic Leukemia Sequencing Illumina HiSeq 2000, Illumina Genome Analyzer II, Illumina HiSeq 2000; 61 bam,srf
EGAD00001000404 Acute myeloid leukaemia (AML) is an aggressive and molecularly diverse disease with a poor overall survival of 20-25%. With an annual incidence of 2.9 per 100,000, AML is currently the commonest myeloid malignancy in Europe, yet the two main therapeutic options for this disease, anthracyclines and purine analogues, have remained unchanged for over 20 years. Currently patients are stratified at diagnosis according to a series of clinicopathological parameters (e.g. age, white cell count and presence/absence of previous clonal haematological disease) and molecular markers (e.g. chromosomal translocations/deletions, aneuploidy and mutations in genes such as FLT3 and NPM1). Patients with adverse prognostic features, whose prognosis is particularly poor (e.g. <15% long-term survival) are offered treatment with allogeneic bone marrow transplantation (allo-BMT) if a sibling or unrelated donor is available. This can significantly improve survival (e.g. up to 40% long-term survival in some contexts), albeit at the expense of significant toxicity and transplant-related mortality (TRM). Allo-BMT is thought to work in part by allowing the delivery of large doses of chemotherapy followed by haemopoietic "rescue" with donor haemopoietic stem cells (haemopoietic failure would otherwise ensue). However, potentially the most potent effect of allo-BMT is the cytotoxic effect of donor lymphocytes against AML blasts, a phenomenon known as graft-vs-leukaemia (GVL) effect. Increasingly, transplants using reduced chemotherapy intensity (mini-allografts) are being used that partially circumvent the toxicity from chemotherapy and rely on GVL to effect cure. Nevertheless, AML relapse after allo-BMT still occurs at a significant rate of up to 80% depending on the type of transplant. There is accumulating evidence that genetic events in residual leukaemic cells enable them to evade immunodetection and therefore survive the GVL effect and expand to cause relapse. The most striking example of this is the loss of HLA antigens after transplants in which donor and recipient are not fully HLA-matched. In these cases, the leukaemia "deletes" the genomic region containing the disparate HLA antigen which was preferentially targeted as "foreign" by the GVL effect. However, the genetic basis of immune evasion in the majority of transplants, which are fully HLA matched, is not known. One possibility is that loss of genes coding for antigens outside the HLA locus but which are also targets of GVL may operate, alternatively genetic events that affect processes downstream of immunological cytotoxicity may be responsible. The identification of genetic events that mediate immune evasion would not only facilitate the understanding of this process but can help plan therapeutic interventions that improve the outcomes of allogeneic transplantation for AML and other disorders. We intend to study this by conducting exome sequencing on 6 cases of AMLs from patients that attend my clinic at Addenbrooke's hospital and have relapsed after allogeneic transplantation. Samples from AML diagnosis, remission/normal and AML relapse (total n=18) will be studied to identify somatic mutations in the primary AML and those acquired by the relapsed clone. The 18 samples will also be studied by array CGH to detect regions of genomic amplification or deletion. Illumina HiSeq 2000; 25 bam
EGAD00001000095 Acute Myeloid Leukemia Sequencing Illumina Genome Analyzer II 9 bam
EGAD00001000101 ADCC Exome Sequencing Illumina Genome Analyzer II, Illumina HiSeq 2000; 125 bam
EGAD00001000062 ADCC Rearrangement Screen Illumina HiSeq 2000, Illumina Genome Analyzer II 14 bam,srf
EGAD00001002192 Additional sequencing data for 173 donors in EGAS00001000154, a study of Pancreatic Ductal Adenocarcinoma. WGS libraries were used for high-cellularity cases, WXS sequencing to high depth on low-cellularity cases. HiSeq 2xxx platform was used in all cases. The analysis files associated with this dataset are merged, de-duplicated bams aligned against GRCh37, one tumour and one normal bam per donor. 346
EGAD00001000764 Adrenocortical carcinomas (ACC) are aggressive cancers originating in the cortex of the adrenal glands. Despite the overall poor prognosis, ACC outcome is heterogeneous. CTNNB1 and TP53 mutations are frequent in these tumors, but the complete spectrum of genetic changes remains undefined. Exome sequencing and SNP array analysis of 45 ACC revealed recurrent alterations in known drivers (CTNNB1, TP53, CDKN2A, RB1, MEN1) and genes not previously reported to be altered in ACC (ZNRF3, DAXX, TERT and MED12), which were validated in an independent cohort of 77 ACC. The cell-surface transmembrane E3 ubiquitin ligase ZNRF36 was the gene the most frequently altered (21%), and appears as a potential novel tumor suppressor gene related to the ß-catenin pathway. Our integrated genomic analyses led to the identification of two distinct molecular subgroups with opposite outcome. The C1A group of poor outcome ACC was characterized by numerous mutations and DNA methylation alterations, whereas the C1B group with good prognosis displayed a specific deregulation of two miRNA clusters. Thus, aggressive and indolent ACC correspond to two distinct molecular entities, driven by different oncogenic alterations. Illumina HiSeq 2000; 45 bam
EGAD00010000164 Affymetrix 6.0 CEL files Affymetrix SNP 6.0 1,992
EGAD00010000158 Affymetrix 6.0 cel files Affymetrix SNP 6.0 1,001
EGAD00010000490 Affymetrix Genome-Wide Human SNP Array 6.0 data Affymetrix 6.0- 19
EGAD00010000442 Affymetrix SNP 6.0 CEL files Affymetrix_SNP6_raw 1,302
EGAD00010000915 Affymetrix SNP6.0 breast cancer genome sequencing data Affymetrix SNP6.0 344
EGAD00010000644 Affymetrix SNP6.0 cancer cell line exome sequencing data 1,022
EGAD00010000498 Affymetrix SNP6.0 genotype data for prostate cancer patients Affymetrix_SNP6- 18
EGAD00000000058 Aggregate results from 22 Carbamazepine-induced hypersensitivity syndrome patients and 2691 UK National Blood Service (NBS) control samples Illumina Infinium 1.2M 2,713
EGAD00000000059 Aggregate results from 43 Carbamazepine-induced hypersensitivity syndrome patients and 1296 1958 British Birth Cohort control samples Affymetrix 500K, Illumina 610K Quad 1,339
EGAD00000000029 Aggregate results from a case-control study on stroke and ischemic stroke. 19,602
EGAD00000000028 Aggregate results from a GWAS study on 3352 cases abd 3145 controls iSelect Beadchip 6,497
EGAD00010000444 Agilent ncRNA 60k txt files Agilent ncRNA 60k 1,480
EGAD00001000289 Agilent whole exome hybridisation capture was performed on genomic DNA derived from cancer and matched normal DNA from the same patients. Next Generation sequencing performed on the resulting exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes. Now we aim to re find and validate the findings of those exome libraries using bespoke pulldown methods and sequencing the products. Illumina HiSeq 2000; 12 bam
EGAD00001000392 Agilent whole exome hybridisation capture was performed on genomic DNA derived from Chondrosarcoma cancer and matched normal DNA from the same patients. Next Generation sequencing performed on the resulting exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes. Now we aim to re find and validate the findings of those exome libraries using bespoke pulldown methods and sequencing the products. Illumina MiSeq; 60 bam
EGAD00001000283 Agilent whole exome hybridisation capture was performed on genomic DNA derived from MDS and matched normal DNA from the same patients. Next Generation sequencing performed on the resulting exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes. Now we aim to discover the prevalence of our findings using bespoke pulldown methods and sequencing the products from a larger set of patient DNA. Illumina HiSeq 2000; 764 bam
EGAD00001000287 Agilent whole exome hybridisation capture will be performed on genomic DNA derived from 25 renal cancers and matched normal DNA from the same patients. Three lanes of Illumina GA sequencing will be performed on the resulting 50 exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes. Illumina Genome Analyzer II; 54 bam,srf
EGAD00001000014 Agilent whole exome hybridisation capture will be performed on genomic DNA derived from 25 renal cancers and matched normal DNA from the same patients. Three lanes of Illumina GA sequencing will be performed on the resulting 50 exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes. Illumina Genome Analyzer II;, Illumina Genome Analyzer II 54 bam,srf
EGAD00001001608 Aligned BAM files of whole exome sequencing of 20 syCRCs and 10 normal counterparts. Each sample of 4 patients (S13, S3, S12 and S6) underwent two sequencing rounds. Illumina HiSeq 2000;, Illumina HiSeq 2500; 42 bam
EGAD00001001435 Aligned whole genome bisulfite sequencing data for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium. 30 bam
EGAD00001000078 ALK inhibitors in the context of ALK-dependent cancer cell lines Illumina HiSeq 2000, Illumina HiSeq 2000; 16 bam,cram
EGAD00010000298 All cases and controls (Hap300) 13,761
EGAD00010000286 All cases and controls (Hap550) Illumina (various) 11,950
EGAD00010000292 All cases and Finnish, Dutch, Italian control samples (Hap300) 10,339
EGAD00010000288 All cases and Finnish, Dutch, Italian control samples (Hap550) 6,313
EGAD00001001380 All humans outside Africa are descendants of the same single exit, usually dated at 50-70 thousand years ago. However, the route taken out of Africa is still debated. The two main candidates are a northern route via Egypt and the Levant, or a southern route via Ethiopia and the Arabian Peninsula. We are generating genetic data to evaluate these two possibilities. In this study we propose to generate high-coverage sequencing data for 3 Egyptian samples. Illumina HiSeq 2000; 3 cram
EGAD00001001372 All humans outside Africa are descendants of the same single exit, usually dated at 50-70 thousand years ago. However, the route taken out of Africa is still debated. The two main candidates are a northern route via Egypt and the Levant, or a southern route via Ethiopia and the Arabian Peninsula. We are generating genetic data to evaluate these two possibilities. In this study we propose to generate low-coverage sequencing data for 100 Egyptian samples. Illumina HiSeq 2000; 100 cram
EGAD00001001921 All pituitary samples Illumina HiSeq 2500; 84 bam
EGAD00001001457 All samples from the "100" project Illumina HiSeq 2000; 238 bam
EGAD00001001210 Altered translation response to stress by medulloblastoma-associated DDX3X mutations 28 bam
EGAD00001000817 Alternative splicing plays critical roles in differentiation, development, and cancer (Pettigrew et al., 2008; Chen and Manley, 2009). The recent identification of specific spliceosome inhibitors has generated interest in the therapeutic potential of targeting this cellular process (van Alphen et al., 2009). Using an integrated genomic approach, we have identified PRPF6, an RNA binding component of the pre-mRNA spliceosome, as an essential driver of oncogenesis in colon cancer. Importantly, PRPF6 is both amplified and overexpressed in colon cancer, and only colon cancer cells with high PRPF6 levels are sensitive to its loss. Our data clearly point to an important role for PRPF6 in colon cancer growth and suggest that a better understanding of its role in alternative splicing in colon cancer is warranted. To determine the specific alternative splice forms that PRPF6 regulates in colon cancer, we plan three experiments: 1. The first involves knocking down expression of PRPF6 in two different cancer cell lines with 3 different siRNAs, and then completing RNA-seq to determine the gene expression changes that occur relative to a non-targeting control siRNA. Because of the role for PRPF6 in pre-mRNA splicing, we especially want to quantify the changes in splice-specific forms of all genes genome-wide to identify genes whose splicing is altered upon PRPF6 knockdown. 2. The second involves immunoprecipitating PRPF6 from two different cancer cell lines and isolating any RNA that is bound to PRPF6, since PRPF6 is an RNA-binding protein. We then want to carry out RNA-seq to identify which RNA molecules co-immunoprecipitated with PRPF6. This will help us determine possible functions for PRPF6 in regulating colon cancer growth. 3. The third involves overexpressing PRPF6 in cell lines and then carrying out RNA-seq to identify any changes in splice-specific gene expression. This will allow us to determine whether increased PRPF6 expression is sufficient to drive alternative splicing changes. Illumina HiSeq 2000; 34 fastq
EGAD00001001873 AML emerges as a consequence of accumulating independent genetic aberrations that direct regulation and/or dysfunction of genes resulting in aberrant activation of signalling pathways, resistance to apoptosis and uncontrolled proliferation. Given the significant heterogeneity of AML genomes, AML patients demonstrate a highly variable response rate and poor median survival in response to current chemotherapy regimens. For the past 4 years we have conducted gene expression profiling on purified bone marrow populations equating to normal haematopoietic stem and progenitor cells from healthy subjects and patients with de novo AML in order to identify AML signatures of aberrantly expressed genes in cancer versus normal. We are now applying a series of bioinformatic methodologies combined with clinical and conventional diagnostic data to establish novel genomics strategies for improved prognostication of AML. Additionally, we use our AML signatures to unravel oncogenic signalling pathway activities in AML patients and test inhibitory drugs for these pathways inn preclinical therapeutic programmes. We consider that superimposing GEP and clinical data for our AML patient cohort with additional data on their mutational status will significantly improve the prognostic power of the study as well as unravel yet unknown mutations associated with aberrant signalling activities of oncogenic pathways. Illumina HiSeq 2000; 215 cram
EGAD00001000253 AML targeted resequencing study Illumina HiSeq 2000; 1,972 bam
EGAD00001000037 An evaluation of different strategies for large-scale pooled sequencing study design. Illumina Genome Analyzer II 7 bam,srf
EGAD00001000087 An exome sequencing pilot study of HIV elite-long term non progressors and rapid progressors Illumina HiSeq 2000 25 bam
EGAD00001000047 An exome sequencing pilot study of HIV elite-long term non progressors and rapid progressors. **ACCESS TO THIS DATASET IS ONLY PROVIDED FOR HIV RELATED RESEARCH** Illumina HiSeq 2000, Illumina HiSeq 2000; 49 bam,cram
EGAD00001000660 Analysis .bam files from HiSeq sequencing of Australian ICGC PDAC study samples, submitted 20130826 353 bam
EGAD00001000030 Analysis of genomic integrity of disease-corrected human induced pluripotent stem cells by exome sequencing Illumina HiSeq 2000 4 bam
EGAD00001000086 Analysis of genomic integrity of disease-corrected human induced pluripotent stem cells by exome sequencing Illumina HiSeq 2000 16 bam
EGAD00001001267 Anaplastic meningiomas are a rare, malignant variant of meningioma. At present there is no effective treatment for this cancer. The aim of the study is to identify somatic mutations in anaplastic meningiomas. We plan to sequence a set of 500 known cancer genes in 50 anaplastic meningioma and corresponding peripheral blood DNA samples. Bioinformatics will be used to analyse the results to assess the probability of these mutations being causal and so likely of critical importance for the tumour growth. Identification of these mutations will guide selection of appropriate compounds to effectively treat the disease. HiSeq X Ten; 60 cram
EGAD00001001452 Anaplastic oligodendrogliomas (AOs) are rare primary brain tumors which are generally incurable, with heterogeneous prognosis and few treatment targets identified. Most oligodendrogliomas have chromosome 1p/19q co-deletion and IDH mutation. We analyzed 51 AOs by whole-exome sequencing, identifying previously reported frequent somatic mutations in CIC and FUBP1. We also identified recurrent mutations in TCF12 and in an additional series of 83 AO. Overall 7.5% of AO are mutated for TCF12, which encodes an oligodendrocyte-related transcription factor. 80% of TCF12 mutations identified were in either the bHLH domain, which is important for TCF12 function as a transcription factor, or were frame shift mutations leading to TCF12 truncated for this domain. We show that these mutations compromise TCF12 transcriptional activity and are associated with a more aggressive tumor type. Our analysis provides further insights into the unique and shared pathways driving AO. Illumina HiSeq 2000; 102 bam
EGAD00010000714 aplastic anemia samples tumor using 250K Affymetrix 250K Nsp-GTYPE 440
EGAD00001001092 Approximately 80% of clinically clearly diagnosed patients suffering from primary ciliary dyskinesia (PCD) cannot be assigned to a specific gene defect. Despite extensive research on PCD and despite the increasing number of PCD genes and knowledge about their sites of action as e.g structural component or cytoplasmic pre-assembly factor, the biology of motile cilia and the pathomechanism leading to PCD is largely unknown. The aim of this study is to identify novel PCD related genes and processes relevant for motile cilia function. We will perform exome sequencing, aiming on the analysis of family trios. In these families, the diagnosis of PCD is secured, but the underlying gene defects has so far not been identified. Illumina HiSeq 2000; 150 cram
EGAD00001002186 Around 10% of patients who present in melanoma clinics have a first degree relative with a previous diagnosis of melanoma. While around 3% have three or more relatives who have been diagnosed with the disease. In this project we will whole genome sequence patients from large Dutch familial melanoma pedigrees to identify mutations in genes that drive melanomagenesis. The identification of these genes will facilitate the management of familial melanoma patients and their families. Illumina HiSeq 2000;, Illumina HiSeq 2500; 38
EGAD00001001271 Around 50 samples of pre-invasive lung cancer lesions showing subsequent clinical and pathological progression or regression HiSeq X Ten; 50 cram
EGAD00010000815 ATL tumor samples using Affymetrix 250K SNP array 1
EGAD00010000813 ATL tumor samples using Illumina 450K Methylation array 1
EGAD00010000811 ATL tumor samples using Illumina 610K SNP array 1
EGAD00001000799 Atrio-ventricular septal defects (AVSD) are a specific form of congenital heart structural defect that result from abnormal or inadequate fusion of endocardial cushions during cardiac development. This project is focused on identifying rare coding variation that substantially increases risk of AVSD, by exome sequencing of AVSD patients and some of their family members, and comparing to control datasets from other sources. The exome sequencing is performed using Agilent SureSelect 50Mb exome v3 and Hiseq 75bp paired reads with an mean sequencing coverage target of 50X. Illumina HiSeq 2000; 95 bam
EGAD00010000789 ATRT expression Illumina Human HT6-v3 Array 4
EGAD00010000790 ATRT expression Illumina Human HT6-v3 Array 41
EGAD00010000712 ATRT genotyping 0
EGAD00010000710 ATRT genotyping blood 0
EGAD00001001444 Atypical teratoid/rhabdoid tumor (ATRT) is one of the most common brain tumors in infants and young children. Although the prognosis of ATRT patients is poor, some patients respond very well to current treatments, suggesting inter-tumor molecular heterogeneity. To investigate this further, we genetically and epigenetically analyzed a large cohort of ATRTs (n = 170). Three distinct molecular subgroups of ATRTs, associated with differences in demographics, tumor location and type of SMARCB1 alterations, were identified using DNA-methylation or gene expression analyses. Whole genome DNA- and RNA-sequencing found no other recurrent mutations explaining the differences between subgroups. However, whole genome bisulfite-sequencing and H3K27Ac ChIP-sequencing of primary tumors revealed clear differences in methylation patterns and enhancer landscapes, leading to the identification of subgroup-specific regulatory networks. Illumina HiSeq 2000;, Illumina HiSeq 2500; 55 fastq
EGAD00001000708 AZIN1 amplicon sequencing data of the EGAS00001000495 project. 454 GS FLX Titanium; 69 fastq
EGAD00001000606 Background Massively parallel sequencing technology has transformed cancer genomics. It is now feasible, in a clinically relevant time-frame, for a clinically manageable cost, to screen DNA from patient tumours for mutations essentially genome-wide. The challenge for personalised medicine will be to increase the sample size to thousands or tens of thousands of well-characterised cases in order to attain sufficient statistical power to stratify patients accurately across the complexity and genomic heterogeneity expected for most of the common tumour types. Currently, whole genome sequencing on this scale is not feasible, and targeted sequencing of relevant portions of the genome will be required. Pilot data We have developed protocols for large-scale, multiplexed sequencing of 100-200 genes in thousands of samples. Essentially, using robotic technology, genomic DNA from the cancer specimen is processed into sequencing libraries with unique DNA barcodes, thereby allowing sequencing reads to be attributed to the sample they derive from. Currently, these sequencing libraries can be generated in a 96-well format using fully automated protocols, and we are exploring methods to expand this to a 384-well format. The sequencing libraries are pooled and hybridized to custom sets of RNA baits representing the genomic regions of interest. Sequencing of the pulled-down libraries is done in pools of 48-96 samples per lane of an Illumina Hi-Seq. This protocol is already implemented at the Sanger Institute. We have published proof that somatic mutations in novel cancer genes can be identified from exome-wide sequencing. In unpublished pilot data, we have established the feasibility of robotic library production, custom pull-down, and multiplexed sequencing of barcoded libraries for 100 known myeloid cancer genes across 760 myelodysplasia samples. Highlights of the data thus far analysed reveal that the coverage is remarkably even between samples; when 96 samples are run, average coverage per lane of sequencing is ~250, with 90-95% of targeted exons covered by >25 reads; known mutations can be discovered in the data set; and the protocol is amenable to whole genome amplified DNA. The bioinformatic algorithms for identification of substitutions and indels in pull-down data are well-established; we have pilot data proving that copy number changes, LOH and genomic rearrangements in specific regions of interest can also be identified by tiling of baits across the relevant loci. Proposal We propose to apply this methodology to 10000 samples from patients with AML enrolled in clinical trials over the last 10-20 years. Oncogenic point mutations and potentially genomic rearrangements will be identified, and linked to clinical outcome data, with a view to undertaking the following sorts of analyses: ? Identification of co-occurrence, mutual exclusivity and clusters of driver mutations. ? Correlation of prognosis with driver mutations and potentially gene-gene interactions ? Exploration of genomic markers of drug response Ultimately, we would like to be in a position to release the mutation data together with matched clinical outcome data to genuine medical researchers via a controlled access approach, possibly within the COSMIC framework (www.sanger.ac.uk/genetics/CGP/cosmic/). The vision here is to generate a portal whereby a clinician faced with an AML patient and his / her mutational profile can obtain a ?personalised? prediction of outcome, together with a fair assessment of the uncertainty of the estimate. With a sufficient sample size, there would also be the potential to develop decision support algorithms for therapeutic choices based on such data. Illumina MiSeq; 38 bam
EGAD00001002179 Background: A rare subgroup of HIV infected individuals naturally controls infection without treatment. These ?elite controllers? constitute an important model for the natural control of HIV infection. Indeed, the study of these individuals may provide insights into strategies for the development of HIV vaccines. Although several HLA and chemokine alleles are known to be over-represented in elite controllers, only a small portion of HIV phenotypic variation is explained by known genetic variants. The elite controller phenotype is rare and distinct, representing the extreme of an infectious disease trait. As such, this phenotype may be partly explained by variation in host immune control, which may be characterized by differences in rare functional genetic variants. Genomic regions underlying elite control can be potentially identified by comparing the presence or frequency of variants in this group to that representing the opposite extreme. In this context, ?rapid progressors? is a group defined by its rapid immunological and clinical disease progression. Aim: To extend an existing study, in order to identify DNA sequence variants involved in the control of HIV infection with greater statistical resolution. Specifically, we aim to sequence up to 200 exomes from multiple cohort studies within the EuroCoord CASCADE collaboration (a collaboration of 25 HIV seroconversion cohort studies across Europe). Illumina HiSeq 2000; 183
EGAD00001001395 Background: Invasive lobular breast cancer (ILBC) is the second most common histological subtype after ductal breast cancer (IDBC). In spite of significant clinical and pathological differences, ILBC is still treated as IDBC. Here, we aimed at identifying recurrent genomic alterations in ILBC with potential clinical implications. Methods: Starting from 630 ILBC primary tumors with a median follow up of 10 years, we interrogated oncogenic substitutions and indels of 360 cancer genes and genome-wide copy number alterations in 413 and 170 ILBC samples, respectively, and correlated those findings with clinical, pathological, and outcome features. The Cancer Genome Atlas database was used for comparison of frequency estimates. Results: Besides the high mutation frequency of CDH1 in 65% of the tumors, alterations in one of the three key genes of the PI3K pathway, PIK3CA, PTEN and AKT1, were present in more than half of the cases. ERBB2 and ERBB3 were mutated in 5.1 and 3.6% of the tumors. FOXA1 mutations and ESR1 copy number gains were detected in 9% and 25% of the samples. All these alterations were more frequent in ILBC than IDBC. The histological diversity of ILBC was associated with specific genomic alterations, such as enrichment for ERBB2 mutations in the mixed, non-classic subtype, and for ARID1A mutations and ESR1 gains in the solid subtype. Finally, ERBB2 and AKT1 mutations were associated with short-term risk of relapse, and chromosome 1q and 11p gain with increased and decreased breast cancer free survival, respectively. Conclusion: ERBB2, ERBB3 and AKT1 mutations represent high prevalence therapeutic targets in ILBC. FOXA1 mutations and ESR1 gains urgently deserve dedicated clinical investigation, especially in the context of endocrine treatment. Illumina HiSeq 2000; 541
EGAD00001001000 Background: The disease course of patients with diffuse low-grade glioma is notoriously unpredictable. Temporal and spatially distinct samples may provide insight into the evolution of clinically relevant copy number aberrations (CNAs). The purpose of this study is to identify CNAs that are indicative of aggressive tumor behaviour and can thereby complement the prognostically favorable 1p/19q co-deletion. Results: Genome-wide, 50 base pair single-end, sequencing was performed to detect CNAs in a clinically well-characterized cohort of 98 formalin-fixed paraffin-embedded low-grade gliomas. CNAs are correlated with overall survival as an endpoint. Seventy-five additional samples from spatially distinct regions and paired recurrent tumors of the discovery cohort were analysed to interrogate the intratumoral heterogeneity and spatial evolution. Loss of 10q25.2-qter is a frequent subclonal event and significantly correlates with an unfavorable prognosis. A significant correlation is furthermore observed in a validation set of 126 and confirmation set of 184 patients. Loss of 10q25.2-qter arises in a longitudinal manner in paired recurrent tumor specimens, whereas the prognostically favorable 1p/ 19q co-deletion is the only CNA that is stable across spatial regions and recurrent tumors. Conclusions: CNAs in low-grade gliomas display extensive intratumoral heterogeneity. Distal loss of 10q is a late onset event and a marker for reduced overall survival in low-grade glioma patients. Intratumoral heterogeneity and higher frequencies of distal 10q loss in recurrences suggest this event is involved in outgrowth to the recurrent tumor. Illumina HiSeq 2000; 175 fastq
EGAD00001001633 BAM files for two WES TRAIP patients Illumina HiSeq 2000; 2 bam
EGAD00001002181 Barrett?s oesophagus is common in the UK affecting 2 % of the population. Family history has been recorded among the 4000 Barrett's cases collected so far and have 241 families. Among them we have assessed 6 multiplex families with proven Barrett?s and defined as having 1 pro band and at least 3 affected first degree members. We propose to exome sequence the probands of these six families to assess the presence of pathogenic rare coding variants. Illumina HiSeq 2000; 6
EGAD00010000916 BASIS breast cancer DNA methylation Illumina 450k Illumina 450k 457
EGAD00001001623 BBMRI - BIOS project - Freeze 1 - Bam files 2,117 bam,contig_fasta
EGAD00001001622 BBMRI - BIOS project - Freeze 1 - Fastq files Illumina HiSeq 2000; 2,199 fastq
EGAD00001000661 Bespoke validation experiments will be performed on ER+ Breast Cancer cases to confirm the presence of mutations found in whole genome sequencing. Illumina HiSeq 2000; 46 bam
EGAD00001001530 Bisulfite-Seq data for 1 Acute Myeloid Leukemia - CTR sample(s). 18 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 Illumina HiSeq 2000; 1 bam
EGAD00001001162 Bisulfite-Seq data for 1 Acute myeloid leukemia sample(s). 18 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 1 bam
EGAD00001000920 Bisulfite-Seq data for 1 alternatively activated macrophage sample(s). 10 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 1 bam,readme_file
EGAD00001001509 Bisulfite-Seq data for 1 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 14 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 Illumina HiSeq 2000; 1 bam
EGAD00001000932 Bisulfite-Seq data for 1 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 14 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 1 bam
EGAD00001001150 Bisulfite-Seq data for 1 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 14 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 1 bam
EGAD00001000921 Bisulfite-Seq data for 1 CD8-positive, alpha-beta T cell sample(s). 14 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 1 bam,readme_file
EGAD00001001563 Bisulfite-Seq data for 1 central memory CD4-positive, alpha-beta T cell sample(s). 15 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 Illumina HiSeq 2000; 1 bam
EGAD00001001553 Bisulfite-Seq data for 1 central memory CD8-positive, alpha-beta T cell sample(s). 13 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 1 bam
EGAD00001001176 Bisulfite-Seq data for 1 class switched memory B cell sample(s). 20 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 1 bam
EGAD00001001567 Bisulfite-Seq data for 1 effector memory CD4-positive, alpha-beta T cell sample(s). 15 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 1 bam
EGAD00001001583 Bisulfite-Seq data for 1 effector memory CD8-positive, alpha-beta T cell sample(s). 11 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 1 bam
EGAD00001001200 Bisulfite-Seq data for 1 effector memory CD8-positive, alpha-beta T cell sample(s). 11 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 1 bam
EGAD00001001541 Bisulfite-Seq data for 1 effector memory CD8-positive, alpha-beta T cell, terminally differentiated sample(s). 15 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 1 bam
EGAD00001001151 Bisulfite-Seq data for 1 endothelial cell of umbilical vein (proliferating) sample(s). 21 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 1 bam
EGAD00001000909 Bisulfite-Seq data for 1 erythroblast sample(s). 14 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 1 bam,readme_file
EGAD00001001587 Bisulfite-Seq data for 1 germinal center B cell sample(s). 6 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 Illumina HiSeq 2000; 1 bam
EGAD00001000943 Bisulfite-Seq data for 1 germinal center B cell sample(s). 8 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 1 bam,readme_file
EGAD00001001203 Bisulfite-Seq data for 1 germinal center B cell sample(s). 8 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 1 bam,readme_file
EGAD00001001493 Bisulfite-Seq data for 1 hematopoietic multipotent progenitor cell sample(s). 5 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 1 bam
EGAD00001000917 Bisulfite-Seq data for 1 hematopoietic multipotent progenitor cell sample(s). 8 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 1 bam,readme_file
EGAD00001001141 Bisulfite-Seq data for 1 hematopoietic multipotent progenitor cell sample(s). 8 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 1 bam,readme_file
EGAD00001000923 Bisulfite-Seq data for 1 macrophage sample(s). 14 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 1 bam,readme_file
EGAD00001001507 Bisulfite-Seq data for 1 mature eosinophil sample(s). 15 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 Illumina HiSeq 2000; 1 bam
EGAD00001001479 Bisulfite-Seq data for 1 memory B cell sample(s). 20 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 Illumina HiSeq 2000; 1 bam
EGAD00001001131 Bisulfite-Seq data for 1 memory B cell sample(s). 20 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 1 bam
EGAD00001001494 Bisulfite-Seq data for 1 memory B cells sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 Illumina HiSeq 2000; 1 bam
EGAD00001001565 Bisulfite-Seq data for 1 monocytes - T=0days sample(s). 15 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 1 bam
EGAD00001001556 Bisulfite-Seq data for 1 naive B cell sample(s). 5 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 1 bam
EGAD00001000927 Bisulfite-Seq data for 1 Plasma cell sample(s). 11 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 1 bam,readme_file
EGAD00001001160 Bisulfite-Seq data for 1 plasma cell sample(s). 11 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 1 bam,readme_file
EGAD00001001529 Bisulfite-Seq data for 1 precursor B cell sample(s). 6 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 1 bam
EGAD00001000910 Bisulfite-Seq data for 1 precursor lymphocyte of B lineage sample(s). 8 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 1 bam,readme_file
EGAD00001001134 Bisulfite-Seq data for 1 precursor lymphocyte of B lineage sample(s). 8 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 1 bam,readme_file
EGAD00001001564 Bisulfite-Seq data for 1 regulatory T cell sample(s). 15 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 1 bam
EGAD00001001180 Bisulfite-Seq data for 2 central memory CD8-positive, alpha-beta T cell sample(s). 27 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 2 bam
EGAD00001001548 Bisulfite-Seq data for 2 class switched memory B cell sample(s). 21 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 2 bam
EGAD00001001497 Bisulfite-Seq data for 2 conventional dendritic cell sample(s). 30 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 2 bam
EGAD00001001473 Bisulfite-Seq data for 2 cytotoxic CD56-dim natural killer cell sample(s). 24 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 2 bam
EGAD00001001510 Bisulfite-Seq data for 2 endothelial cell of umbilical vein (proliferating) sample(s). 36 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 Illumina HiSeq 2000; 2 bam
EGAD00001001486 Bisulfite-Seq data for 2 endothelial cell of umbilical vein (resting) sample(s). 2 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 Illumina HiSeq 2000; 2 bam
EGAD00001001135 Bisulfite-Seq data for 2 endothelial cell of umbilical vein (resting) sample(s). 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 2 bam
EGAD00001001484 Bisulfite-Seq data for 2 erythroblast sample(s). 35 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 Illumina HiSeq 2000; 2 bam
EGAD00001001133 Bisulfite-Seq data for 2 erythroblast sample(s). 35 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 2 bam,readme_file
EGAD00001000934 Bisulfite-Seq data for 2 Multiple myeloma sample(s). 16 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 2 bam,readme_file
EGAD00001001152 Bisulfite-Seq data for 2 Multiple myeloma sample(s). 16 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 2 bam,readme_file
EGAD00001001522 Bisulfite-Seq data for 2 plasma cell sample(s). 17 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 2 bam
EGAD00001001537 Bisulfite-Seq data for 3 Acute promyelocytic leukemia sample(s). 24 run(s), 3 experiment(s), 3 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 3 bam
EGAD00001001167 Bisulfite-Seq data for 3 Acute promyelocytic leukemia sample(s). 24 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 3 bam
EGAD00001001205 Bisulfite-Seq data for 3 CD38-negative naive B cell sample(s). 29 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 3 bam
EGAD00001001516 Bisulfite-Seq data for 3 CD4-positive, alpha-beta T cell sample(s). 61 run(s), 3 experiment(s), 3 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 3 bam
EGAD00001001157 Bisulfite-Seq data for 3 CD4-positive, alpha-beta T cell sample(s). 61 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 3 bam
EGAD00001001128 Bisulfite-Seq data for 3 cytotoxic CD56-dim natural killer cell sample(s). 38 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 3 bam
EGAD00001000914 Bisulfite-Seq data for 3 inflammatory macrophage sample(s). 38 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 3 bam,readme_file
EGAD00001001139 Bisulfite-Seq data for 3 inflammatory macrophage sample(s). 38 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 3 bam,readme_file
EGAD00001001143 Bisulfite-Seq data for 4 alternatively activated macrophage sample(s). 64 run(s), 4 experiment(s), 4 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 4 bam,readme_file
EGAD00001001590 Bisulfite-Seq data for 4 CD38-negative naive B cell sample(s). 44 run(s), 4 experiment(s), 4 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 4 bam
EGAD00001001571 Bisulfite-Seq data for 4 CD8-positive, alpha-beta T cell sample(s). 56 run(s), 4 experiment(s), 4 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 Illumina HiSeq 2000; 4 bam
EGAD00001001189 Bisulfite-Seq data for 4 CD8-positive, alpha-beta T cell sample(s). 56 run(s), 4 experiment(s), 4 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 4 bam,readme_file
EGAD00001001498 Bisulfite-Seq data for 5 alternatively activated macrophage sample(s). 79 run(s), 5 experiment(s), 5 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 5 bam
EGAD00001001192 Bisulfite-Seq data for 5 macrophage sample(s). 72 run(s), 5 experiment(s), 5 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 5 bam,readme_file
EGAD00001001482 Bisulfite-Seq data for 6 Acute Myeloid Leukemia sample(s). 66 run(s), 6 experiment(s), 6 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 6 bam
EGAD00001000941 Bisulfite-Seq data for 6 CD14-positive, CD16-negative classical monocyte sample(s). 86 run(s), 6 experiment(s), 6 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 6 bam,readme_file
EGAD00001001206 Bisulfite-Seq data for 6 CD14-positive, CD16-negative classical monocyte sample(s). 86 run(s), 6 experiment(s), 6 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 6 bam,readme_file
EGAD00001001491 Bisulfite-Seq data for 6 inflammatory macrophage sample(s). 83 run(s), 6 experiment(s), 6 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 6 bam
EGAD00001001585 Bisulfite-Seq data for 6 mature neutrophil sample(s). 79 run(s), 6 experiment(s), 6 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 6 bam
EGAD00001000935 Bisulfite-Seq data for 6 mature neutrophil sample(s). 79 run(s), 6 experiment(s), 6 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 6 bam,readme_file
EGAD00001001201 Bisulfite-Seq data for 6 mature neutrophil sample(s). 79 run(s), 6 experiment(s), 6 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811 Illumina HiSeq 2000; 6 bam,readme_file
EGAD00001001591 Bisulfite-Seq data for 7 CD14-positive, CD16-negative classical monocyte sample(s). 101 run(s), 7 experiment(s), 7 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 7 bam
EGAD00001001575 Bisulfite-Seq data for 8 macrophage sample(s). 117 run(s), 8 experiment(s), 8 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820 8 bam
EGAD00001001261 Bisulfite-Seq of CD14-positive, CD16-negative classical monocyte samples for methylome saturation and COMET analysis Illumina HiSeq 2000; 2 bam,readme_file
EGAD00001000406 Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare and aggressive haematological malignancy derived from precursors of plasmacytoid dendritic cells. Due to the rarity of BPDCNs our knowledge of their molecular pathogenesis was until recently confined to observations describing reccurent chromosomal deletions involving chromosomes 5q, 12p, 13q, 6q, 15q and 9. A recent publication went on to delineate the common deleted regions using aCGH and demonstrated that these centred around known tumour suppressor genes including CDKN2A/B (9p21.3), RB1 (12p13.2-14.3), CDKN1B (13q11-q12) and IKZF1 (7p12.2). These mutations are found recurrently in several different cancers and in most cases are thought to be involved in tumour progression rather than initiation. However, the well-defined nature and cellular ontogeny of these neoplasms suggests strongly that they share one or a few characteristic mutations as has been demonstrated for other uncommon but well-defined neoplasms such as Hairy Cell Leukemia (BRAF) and ovarian Granulosa Cell tumours (FOXL2). Illumina HiSeq 2000; 14 bam
EGAD00001000040 Bleeding Illumina Genome Analyzer II 6 bam
EGAD00001000140 Blood sample of serious ovarian carcinoma patient Complete Genomics 1 CompleteGenomics_native
EGAD00010000476 blood-based gene expression from breast cancer cases and age-matched controls in case-control serie 1 (CC1) Illumina 110
EGAD00010000474 blood-based gene expression from breast cancer cases and age-matched controls in case-control serie 2 (CC2) Illumina 98
EGAD00010000478 blood-based gene expression from breast cancer cases and age-matched controls in case-control serie 3 (CC3) Illumina 118
EGAD00010000716 BLUEPRINT DNA Methylation of different B-cell subpopulations 35
EGAD00010000831 BLUEPRINT EpiMatch: harnessing epigenetics for hematopoietic stem cell transplantation Illumina Infinium HumanMethylation450 BeadChips 85
EGAD00010000718 BLUEPRINT Gene expression of different B-cell subpopulations 42
EGAD00001002051 BRAF V600E colorectal cancers do not respond to the only currently FDA approved targeted therapy for CRC. There is currently a trial underway in the UK recruiting V600E CRC patients for treatment with a triple therapy combination of Cetuximab, Trametinib and Dabrafenib. We have mutagenized a pool of V600E CRC cell lines and treated with this triple therapy to select out drug resistant clones. We will now sequence these drug resistant clones with the aim of identifying common point mutations engendering resistance to this new therapy. Illumina HiSeq 2500; 20
EGAD00001001274 Brain samples for this dataset were provided by the Medical Research Council Sudden Death Brain and Tissue Bank (Edinburgh, UK). All four individuals sampled were of European descent, neurologically normal during life and confirmed to be neuropathologically normal by a consultant neuropathologist using histology performed on sections prepared from paraffin-embedded tissue blocks. Twelve regions of the central nervous system were sampled from each individual. The regions studied were: cerebellar cortex, frontal cortex, temporal cortex, occipital cortex, hippocampus, the inferior olivary nucleus (sub-dissected from the medulla), putamen, substantia nigra, thalamus, hypothalamus, intralobular white matter and cervical spinal cord. Illumina HiSeq 2000; 48 bam
EGAD00001000093 Breast Cancer Exome Resequencing Illumina Genome Analyzer II 21 bam
EGAD00001000110 Breast Cancer Exome Sequencing Illumina HiSeq 2000, Illumina Genome Analyzer II 179 bam
EGAD00001000066 Breast Cancer Follow Up Series Illumina Genome Analyzer II 288 bam
EGAD00001000130 Breast Cancer Matched Pair Cell Line Whole Genomes Illumina HiSeq 2000, Illumina HiSeq 2000; 22 bam
EGAD00001000121 Breast Cancer Whole Genome Sequencing Illumina HiSeq 2000 6 bam
EGAD00010000942 Breast lesions assayed with Affymetrix SNP 6.0 Affymetrix SNP 6.0 125
EGAD00001000127 Burden of Disease in Sarcoma Illumina HiSeq 2000, Illumina HiSeq 2000; 220 bam,cram
EGAD00010000387 Cambridge control samples using a 1.2M genotyping chip from Illumina Illumina Human 1.2M Duo custom BeadChips v1 - Genome Studio 188
EGAD00010000389 Cambridge control samples using a 24k expression array from Illumina Illumina Human-Ref 8 v3.0 expression array 395
EGAD00010000391 Cambridge control samples using a 660K genotyping chip from Illumina Illumina Human 660K Quad BeadChips - Illuminus 232
EGAD00001001935 Cancer amplicon reads consisting of BAM paired end reads from primary multiple myeloma samples. Illumina MiSeq; 88 bam
EGAD00001001058 Cancer exome reads consisting of FASTQ paired end reads from bone marrow samples Illumina HiSeq 2000; 42 fastq
EGAD00001000092 Cancer Exome Resequencing Illumina Genome Analyzer II 58 bam
EGAD00001001930 Cancer genes can affect ribosomal RNA processing and this can underlie their essentiality to cells, making them cell-essential in the same way as ribosomal genes themselves. We want to confirm this, in order to understand the results of our CRISPR drop-out screens. NOTE FROM BESPOKE TEAM: Run a single read 1 (forward read) of 30 bases, then an index 1 read as normal. This would fit a 50cycle kit Illumina MiSeq; 6 cram
EGAD00001000094 Cancer Genome Libraries Tests Illumina Genome Analyzer II 16 bam
EGAD00001000308 Cancer Genome Scanning in Plasma: Detection of Tumor-Associated Copy Number Aberrations, Single-Nucleotide Variants, and Tumoral Heterogeneity by Massively Parallel Sequencing 1 bam
EGAD00001000284 Cancer Genome Scanning in Plasma: Detection of Tumor-Associated Copy Number Aberrations, Single-Nucleotide Variants, and Tumoral Heterogeneity by Massively Parallel Sequencing Illumina Genome Analyzer IIx; 1
EGAD00001000290 Cancer Genome Scanning in Plasma: Detection of Tumor-Associated Copy Number Aberrations, Single-Nucleotide Variants, and Tumoral Heterogeneity by Massively Parallel Sequencing Illumina Genome Analyzer IIx; 1
EGAD00001000389 Cancer is driven by mutations in the genome. We will uncover the mutations that give rise to Ewing's sarcoma, a bone tumour that largely affects children. We will use second generation Illumina massively parallel sequencing, and bespoke software, to characterise the genomes and transcriptomes of Ewing's sarcoma tumours. Illumina HiSeq 2000; 20 bam
EGAD00001000444 Cancer is driven my mutations in the genome. We will uncover the mutations that give rise to Ewing's sarcoma, a bone tumour that largely affects children. We will use second generation Illumina massively parallel sequencing, and bespoke software, to characterise the genomes and transcriptomes of Ewing's sarcoma tumours. Illumina HiSeq 2000; 3 bam
EGAD00001000067 Cancer Single Cell Sequencing Illumina HiSeq 2000, Illumina HiSeq 2000; 16 bam,srf
EGAD00001000898 Cancers are ecosystems of genetically related clones, competing across space and time for limited resources. To understand the clonal structure of primary breast cancer, we applied genome and targeted sequencing to 295 samples from 49 patients’ tumors. The extent of subclonal diversification varied considerably among patients and encompassed many spatial patterns, including local growth, intraductal dissemination and clonal intermixture. Landmarks of disease progression, such as acquiring invasive or metastatic potential, arose within detectable subclones of antecedent lesions, suggesting that subclonal mutations could be relevant if actionable. No defined temporal order of mutation was evident, with the commonest genes, including PIK3CA, TP53, BRCA2, PTEN and MYC, mutated early in some, late in others, often exhibiting parallel evolution across subclones. Signatures of homologous recombination deficiency correlated with response to neoadjuvant chemotherapy. Thus, the interplay of mutation, growth and competition drives clonal structures of breast cancer that are complex, variable across patients and clinically relevant. Illumina HiSeq 2000; 42 bam
EGAD00001000965 Cancers are ecosystems of genetically related clones, competing across space and time for limited resources. To understand the clonal structure of primary breast cancer, we applied genome and targeted sequencing to 295 samples from 49 patients’ tumors. The extent of subclonal diversification varied considerably among patients and encompassed many spatial patterns, including local growth, intraductal dissemination and clonal intermixture. Landmarks of disease progression, such as acquiring invasive or metastatic potential, arose within detectable subclones of antecedent lesions, suggesting that subclonal mutations could be relevant if actionable. No defined temporal order of mutation was evident, with the commonest genes, including PIK3CA, TP53, BRCA2, PTEN and MYC, mutated early in some, late in others, often exhibiting parallel evolution across subclones. Signatures of homologous recombination deficiency correlated with response to neoadjuvant chemotherapy. Thus, the interplay of mutation, growth and competition drives clonal structures of breast cancer that are complex, variable across patients and clinically relevant. Illumina HiSeq 2000; 331 bam,cram
EGAD00001001243 Capture Hi-C identifies the chromatin interactome of colorectal cancer risk loci. Illumina HiSeq 2000; 9 bam,fastq
EGAD00010000371 Case and control samples (Genotypes) Infinium_370k - GenomeStudio 170
EGAD00010000202 Case samples (Illumina_660K & Illumina_670K) Illumina_660K/Illumina_670K 1,478
EGAD00010000512 Case samples using HumanOmni1-Quad GenomeWideSNP_6-BirdseedV2 12
EGAD00010000514 Case samples using SNP 6.0 Array GenomeWideSNP_6-BirdseedV2 12
EGAD00010000656 Case samples using SNP 6.0 Array 20
EGAD00010000502 Case samples using SNP Array 6.0 Affymetrix_U133plus2- 35
EGAD00010000500 Case samples using U133 Plus 2.0 Array Affymetrix_U133plus2- 35
EGAD00010000492 Cases_Human660W-Quad_v1_A Illumina_Human660W-Quad_v1_A-Not supplied 4
EGAD00010000480 ccRCC case samples using 250K Nsp Affymetrix_250K(Nsp) - gtype 240
EGAD00010000486 ccRCC case samples using expression array Agilent Human Whole Genome 4x44k v2 - Feature Extraction 101
EGAD00010000482 ccRCC case samples using methylation array Illumina Infinium HumanMethylation 450K - GenomeStudio 1
EGAD00010000484 ccRCC control samples using 250K Nsp Affymetrix_250K(Nsp) - gtype 234
EGAD00010000612 Celiac disease North Indian samples using Immunochip 1,227
EGAD00010000051 Cell line derived from microdissected primary pancreatic ductal adenocarcinoma tissues Affymetrix SNP 6.0 15
EGAD00001000064 Cell Line Sub Clone Rearrangement Screen Illumina Genome Analyzer II 6 bam
EGAD00010000130 Cerebellar ataxia, mental retardation, and disequilibrium syndrome (CAMRQ) samples Illumina 300 Duo V2 - Bead Studio, Illumina 2
EGAD00001002065 Cetuximab is a targeted monoclonal antibody against the epidermal growth factor receptor (EGFR) which is used therapeutically for the treatment of KRAS wild-type colorectal cancer (CRC). The Cetuximab sensitive KRAS wild-type CRC cell line NCI-H508 has been treated with a fixed concentration of ENU for 24 hours and then selected with Cetuximab until drug resistant clones were ready to be picked and grown up as sub-clones of the parental cell line. These will have genes causally implicated in cancer sequenced to identify common point mutations in multiple independently derived drug resistant clones as a forward genetic screen for mechanisms of resistance to Cetuximab in CRC Illumina HiSeq 2500; 50
EGAD00001001948 Cetuximab is a targeted monoclonal antibody against the epidermal growth factor receptor (EGFR) which is used therapeutically for the treatment of KRAS wild-type colorectal cancer (CRC). The Cetuximab sensitive KRAS wild-type CRC cell line NCI-H508 has been treated with a fixed concentration of ENU for 24 hours and then selected with Cetuximab until drug resistant clones were ready to be picked and grown up as sub-clones of the parental cell line. These will have genes causally implicated in cancer sequenced to identify common point mutations in multiple independently derived drug resistant clones as a forward genetic screen for mechanisms of resistance to Cetuximab in CRC Illumina HiSeq 2000; 16 cram
EGAD00001001947 Cetuximab is a targeted monoclonal antibody against the epidermal growth factor receptor (EGFR) which is used therapeutically for the treatment of KRAS wild-type colorectal cancer (CRC). The Cetuximab sensitive KRAS wild-type CRC cell line NCI-H508 has been treated with a fixed concentration of ENU for 24 hours and then selected with Cetuximab until drug resistant clones were ready to be picked and grown up as sub-clones of the parental cell line. These will have genes causally implicated in cancer sequenced to identify common point mutations in multiple independently derived drug resistant clones as a forward genetic screen for mechanisms of resistance to Cetuximab in CRC. Illumina HiSeq 2000; 16 cram
EGAD00001000658 Changes in gene dosage are a major driver of cancer1, engineered from a finite, but increasingly well annotated, repertoire of mutational mechanisms2-6. These processes operate over levels ranging from individual exons to whole chromosomes, often generating correlated copy number alterations across hundreds of linked genes. An example of the latter is the 2% of childhood acute lymphoblastic leukemia (ALL) characterized by recurrent intrachromosomal amplification of megabase regions of chromosome 21 (iAMP21)7,8 To dissect the interplay between mutational processes and selection on this scale, we used genomic, cytogenetic and transcriptional analysis, coupled with novel bioinformatic approaches, to reconstruct the evolution of iAMP21 ALL. We find that individuals born with the rare constitutional Robertsonian translocation between chromosomes 15 and 21, rob(15;21)(q10;q10)c, have ~2700-fold increased risk of developing iAMP21 ALL compared to the general population. In such cases, amplification is initiated by chromothripsis involving both sister chromatids of the dicentric Robertsonian chromosome. In contrast, sporadic iAMP21 is typically initiated by breakage-fusion-bridge (BFB) events, often followed by chromothripsis or other rearrangements. In both sporadic and iAMP21 in rob(15;21)c individuals, the final stages of amplification frequently involve large-scale duplications of the abnormal chromosome. The end-product is a derivative chromosome 21 or a derivative originating from the rob(15;21)c chromosome, der(15;21), respectively, with gene dosage optimised for leukemic potential, showing constrained copy number levels over multiple linked genes. In summary, the constitutional translocation, rob(15;21)c, predisposes to leukemia through a novel mechanism, namely a propensity to undergo chromothripsis, likely related to its dicentric nature. More generally, our data illustrate that several cancer-specific mutational processes, applied sequentially, can co-ordinate to fashion copy number profiles over large genomic scales, incrementally refining the fitness benefits of aggregated gene dosage changes. Illumina Genome Analyzer II;, Illumina HiSeq 2000; 9 bam
EGAD00001001229 ChIP-Seq (H3K27ac) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium. Illumina HiSeq 2000; 48 bam
EGAD00001001230 ChIP-Seq (H3K27me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium. Illumina HiSeq 2000; 48 bam
EGAD00001001231 ChIP-Seq (H3K36me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium. Illumina HiSeq 2000; 48 bam
EGAD00001001232 ChIP-Seq (H3K4me1) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium. Illumina HiSeq 2000; 48 bam
EGAD00001001233 ChIP-Seq (H3K4me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium. Illumina HiSeq 2000; 48 bam
EGAD00001002238 ChIP-Seq (H3K4me3, H3K4me1, H3K9me3, H3K27ac, H3K27me3, H3K36me3, Input) data for HL60 cell line generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency. Illumina HiSeq 2000; 1
EGAD00001001234 ChIP-Seq (H3K9me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium. Illumina HiSeq 2000; 48 bam
EGAD00001001235 ChIP-Seq (Input) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium. 48 bam
EGAD00001001569 ChIP-Seq data for 1 Acute lymphocytic leukemia - CTR sample(s). 7 run(s), 7 experiment(s), 7 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 1 fastq
EGAD00001001536 ChIP-Seq data for 1 Acute Myeloid Leukemia - MC2884 sample(s). 2 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 Illumina HiSeq 2000; 1 fastq
EGAD00001001554 ChIP-Seq data for 1 adult endothelial progenitor cell sample(s). 8 run(s), 7 experiment(s), 7 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 1 fastq
EGAD00001001570 ChIP-Seq data for 1 CD3-negative, CD4-positive, CD8-positive, double positive thymocyte sample(s). 2 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 Illumina HiSeq 2000; 1 fastq
EGAD00001001503 ChIP-Seq data for 1 CD3-positive, CD4-positive, CD8-positive, double positive thymocyte sample(s). 3 run(s), 3 experiment(s), 3 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 Illumina HiSeq 2000; 1 fastq
EGAD00001001557 ChIP-Seq data for 1 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 7 run(s), 6 experiment(s), 6 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 1 fastq
EGAD00001000916 ChIP-Seq data for 1 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 7 run(s), 7 experiment(s), 7 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 1 fastq
EGAD00001001182 ChIP-Seq data for 1 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 7 run(s), 7 experiment(s), 7 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 1 fastq
EGAD00001001584 ChIP-Seq data for 1 CD4-positive, alpha-beta thymocyte sample(s). 2 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 Illumina HiSeq 2000; 1 fastq
EGAD00001001568 ChIP-Seq data for 1 CD8-positive, alpha-beta thymocyte sample(s). 2 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 Illumina HiSeq 2000; 1 fastq
EGAD00001001144 ChIP-Seq data for 1 central memory CD4-positive, alpha-beta T cell sample(s). 6 run(s), 6 experiment(s), 6 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 1 fastq
EGAD00001001499 ChIP-Seq data for 1 central memory CD4-positive, alpha-beta T cell sample(s). 9 run(s), 7 experiment(s), 7 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 Illumina HiSeq 2000; 1 fastq
EGAD00001001577 ChIP-Seq data for 1 effector memory CD8-positive, alpha-beta T cell, terminally differentiated sample(s). 4 run(s), 4 experiment(s), 4 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 Illumina HiSeq 2000; 1 fastq
EGAD00001001195 ChIP-Seq data for 1 effector memory CD8-positive, alpha-beta T cell, terminally differentiated sample(s). 4 run(s), 4 experiment(s), 4 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 1 fastq
EGAD00001001528 ChIP-Seq data for 1 Leukemia sample(s). 2 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 Illumina HiSeq 2000; 1 fastq
EGAD00001000929 ChIP-Seq data for 1 macrophage sample(s). 6 run(s), 6 experiment(s), 6 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 1 fastq
EGAD00001000906 ChIP-Seq data for 1 mature eosinophil sample(s). 7 run(s), 7 experiment(s), 7 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 1 fastq
EGAD00001001578 ChIP-Seq data for 1 mesenchymal stem cell of the bone marrow sample(s). 9 run(s), 7 experiment(s), 7 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 1 fastq
EGAD00001001179 ChIP-Seq data for 10 CD14-positive, CD16-negative classical monocyte sample(s). 73 run(s), 69 experiment(s), 69 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 10 fastq
EGAD00001001576 ChIP-Seq data for 12 macrophage sample(s). 49 run(s), 49 experiment(s), 49 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 12 fastq
EGAD00001001196 ChIP-Seq data for 13 macrophage sample(s). 55 run(s), 55 experiment(s), 55 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000;, NextSeq 500; 13 fastq
EGAD00001001481 ChIP-Seq data for 15 Acute Myeloid Leukemia sample(s). 75 run(s), 72 experiment(s), 72 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 16 fastq
EGAD00001000936 ChIP-Seq data for 2 CD8-positive, alpha-beta T cell sample(s). 13 run(s), 13 experiment(s), 13 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 2 fastq
EGAD00001001472 ChIP-Seq data for 2 effector memory CD8-positive, alpha-beta T cell sample(s). 10 run(s), 10 experiment(s), 10 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 2 fastq
EGAD00001001127 ChIP-Seq data for 2 effector memory CD8-positive, alpha-beta T cell sample(s). 10 run(s), 10 experiment(s), 10 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 2 fastq
EGAD00001001487 ChIP-Seq data for 2 endothelial cell of umbilical vein (proliferating) sample(s). 12 run(s), 12 experiment(s), 12 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 2 fastq
EGAD00001001136 ChIP-Seq data for 2 endothelial cell of umbilical vein (proliferating) sample(s). 13 run(s), 13 experiment(s), 13 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 2 fastq
EGAD00001001183 ChIP-Seq data for 2 endothelial cell of umbilical vein (resting) sample(s). 10 run(s), 10 experiment(s), 10 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 2 fastq
EGAD00001001559 ChIP-Seq data for 2 endothelial cell of umbilical vein (resting) sample(s). 11 run(s), 11 experiment(s), 11 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 Illumina HiSeq 2000; 2 fastq
EGAD00001001574 ChIP-Seq data for 2 erythroblast sample(s). 12 run(s), 12 experiment(s), 12 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 2 fastq
EGAD00001000924 ChIP-Seq data for 2 erythroblast sample(s). 14 run(s), 14 experiment(s), 14 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 2 fastq
EGAD00001001194 ChIP-Seq data for 2 erythroblast sample(s). 14 run(s), 14 experiment(s), 14 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 2 fastq
EGAD00001001502 ChIP-Seq data for 2 germinal center B cell sample(s). 12 run(s), 11 experiment(s), 11 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 2 fastq
EGAD00001001539 ChIP-Seq data for 2 mature eosinophil sample(s). 12 run(s), 12 experiment(s), 12 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 2 fastq
EGAD00001001168 ChIP-Seq data for 2 mature eosinophil sample(s). 12 run(s), 12 experiment(s), 12 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 2 fastq
EGAD00001001580 ChIP-Seq data for 2 monocyte sample(s). 6 run(s), 6 experiment(s), 6 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 Illumina HiSeq 2000;, NextSeq 500; 2 fastq
EGAD00001001197 ChIP-Seq data for 2 monocyte sample(s). 7 run(s), 7 experiment(s), 7 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000;, NextSeq 500; 2 fastq
EGAD00001001592 ChIP-Seq data for 2 Multiple myeloma sample(s). 16 run(s), 14 experiment(s), 14 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 2 fastq
EGAD00001001470 ChIP-Seq data for 2 plasma cell sample(s). 13 run(s), 12 experiment(s), 12 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 2 fastq
EGAD00001001485 ChIP-Seq data for 3 Acute Myeloid Leukemia - SAHA sample(s). 11 run(s), 11 experiment(s), 11 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 3 fastq
EGAD00001000925 ChIP-Seq data for 3 CD4-positive, alpha-beta T cell sample(s). 21 run(s), 21 experiment(s), 21 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 3 fastq
EGAD00001001187 ChIP-Seq data for 3 Chronic lymphocytic leukemia sample(s). 6 run(s), 6 experiment(s), 6 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 3 fastq
EGAD00001000940 ChIP-Seq data for 3 inflammatory macrophage sample(s). 21 run(s), 21 experiment(s), 21 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 3 fastq
EGAD00001001527 ChIP-Seq data for 3 mature neutrophil - G-CSF/Dex. Treatment (16-20 hrs) sample(s). 18 run(s), 18 experiment(s), 18 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 3 fastq
EGAD00001001533 ChIP-Seq data for 4 Acute Myeloid Leukemia - CTR sample(s). 21 run(s), 21 experiment(s), 21 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 4 fastq
EGAD00001001514 ChIP-Seq data for 4 alternatively activated macrophage sample(s). 22 run(s), 22 experiment(s), 22 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 4 fastq
EGAD00001000938 ChIP-Seq data for 4 alternatively activated macrophage sample(s). 29 run(s), 28 experiment(s), 28 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 4 fastq
EGAD00001001511 ChIP-Seq data for 4 band form neutrophil sample(s). 18 run(s), 17 experiment(s), 17 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 4 fastq
EGAD00001001207 ChIP-Seq data for 4 CD38-negative naive B cell sample(s). 14 run(s), 14 experiment(s), 14 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 4 fastq
EGAD00001001158 ChIP-Seq data for 4 cytotoxic CD56-dim natural killer cell sample(s). 16 run(s), 16 experiment(s), 16 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 4 fastq
EGAD00001001518 ChIP-Seq data for 4 cytotoxic CD56-dim natural killer cell sample(s). 17 run(s), 17 experiment(s), 17 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 4 fastq
EGAD00001001495 ChIP-Seq data for 4 neutrophilic metamyelocyte sample(s). 18 run(s), 12 experiment(s), 12 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 4 fastq
EGAD00001001517 ChIP-Seq data for 4 neutrophilic myelocyte sample(s). 14 run(s), 14 experiment(s), 14 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 4 fastq
EGAD00001001588 ChIP-Seq data for 4 segmented neutrophil of bone marrow sample(s). 20 run(s), 19 experiment(s), 19 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 4 fastq
EGAD00001001155 ChIP-Seq data for 5 alternatively activated macrophage sample(s). 36 run(s), 35 experiment(s), 35 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 5 fastq
EGAD00001001513 ChIP-Seq data for 5 CD8-positive, alpha-beta T cell sample(s). 26 run(s), 26 experiment(s), 26 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 5 fastq
EGAD00001001154 ChIP-Seq data for 5 CD8-positive, alpha-beta T cell sample(s). 28 run(s), 28 experiment(s), 28 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 5 fastq
EGAD00001001562 ChIP-Seq data for 5 Chronic lymphocytic leukemia sample(s). 24 run(s), 23 experiment(s), 23 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 5 fastq
EGAD00001001138 ChIP-Seq data for 6 Acute promyelocytic leukemia sample(s). 25 run(s), 23 experiment(s), 23 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 6 fastq
EGAD00001001490 ChIP-Seq data for 6 Acute promyelocytic leukemia sample(s). 29 run(s), 27 experiment(s), 27 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 6 fastq
EGAD00001001594 ChIP-Seq data for 6 CD38-negative naive B cell sample(s). 20 run(s), 20 experiment(s), 20 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 6 fastq
EGAD00001001204 ChIP-Seq data for 6 inflammatory macrophage sample(s). 35 run(s), 35 experiment(s), 35 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 6 fastq
EGAD00001001519 ChIP-Seq data for 6 naive B cell sample(s). 34 run(s), 28 experiment(s), 28 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 6 fastq
EGAD00001001188 ChIP-Seq data for 7 Acute myeloid leukemia sample(s). 23 run(s), 23 experiment(s), 23 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 7 fastq
EGAD00001001505 ChIP-Seq data for 7 CD4-positive, alpha-beta T cell sample(s). 39 run(s), 39 experiment(s), 39 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 7 fastq
EGAD00001001147 ChIP-Seq data for 7 CD4-positive, alpha-beta T cell sample(s). 46 run(s), 45 experiment(s), 45 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 7 fastq
EGAD00001001589 ChIP-Seq data for 7 inflammatory macrophage sample(s). 36 run(s), 36 experiment(s), 36 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 7 fastq
EGAD00001000930 ChIP-Seq data for 7 mature neutrophil sample(s). 68 run(s), 50 experiment(s), 50 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 7 fastq
EGAD00001001149 ChIP-Seq data for 7 mature neutrophil sample(s). 78 run(s), 60 experiment(s), 60 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 7 fastq
EGAD00001001552 ChIP-Seq data for 9 CD14-positive, CD16-negative classical monocyte sample(s). 56 run(s), 53 experiment(s), 53 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 9 fastq
EGAD00001000913 ChIP-Seq data for 9 CD14-positive, CD16-negative classical monocyte sample(s). 59 run(s), 55 experiment(s), 55 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811 Illumina HiSeq 2000; 9 fastq
EGAD00001001508 ChIP-Seq data for 9 mature neutrophil sample(s). 48 run(s), 45 experiment(s), 45 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820 9 fastq
EGAD00001000676 ChIP-seq for monocytes and neutrophils Illumina HiSeq 2000; 14 fastq
EGAD00001002135 ChIPseq data of Atypical teratoid/rhabdoid tumors (ATRT) Illumina HiSeq 2000;, Illumina HiSeq 2500; 15
EGAD00001002012 ChIPseq data of whole blood samples from smoking and non-smoking mothers and their children at gestation/birth and follow-up years. 16
EGAD00010000488 Chondroblastoma case sample genotype using Affymetrix SNP6.0 Affymetrix_SNP6- 7
EGAD00001001063 Chondromxoid fibroma is a benign tumour of bone with unknown underlying pathogenesis. To determine pathognomic genomic event in chondromyxoid fibroma whole genome sequencing will be undertaken to reconstruct rearrangements and find underlying mutations. Illumina HiSeq 2000; 2 bam,cram
EGAD00001000358 Chondrosarcoma (CHS) is a heterogeneous collection of malignant bone tumours and is the second most common primary malignancy of bone after osteosarcoma. Recent work has identified frequent, recurrent mutations in IDH1/2 in nearly half of central CHS. However, there has been little systematic genomic analysis of this tumour type and thus the contribution of other genes is unclear. Here we report comprehensive genomic analyses of 49 cases of CHS. We identified hypermutability of the major cartilage collagen COL2A1 with insertions, deletions and rearrangements identified in 37% of cases. The patterns of mutation were consistent with selection for variants likely to impair normal collagen biosynthesis. In addition we identified mutations in IDH1/2 (59%), TP53 (20%), the RB1 pathway (27%) and hedgehog signaling (22%). Illumina HiSeq 2000; 17 bam
EGAD00010000452 Chondrosarcoma case sample genotype using Affymetrix SNP6.0 Affymetrix_SNP6 36
EGAD00001000125 Chondrosarcoma Exome Illumina HiSeq 2000, Illumina HiSeq 2000; 104 bam
EGAD00001000119 Chordoma Exome Sequencing Illumina HiSeq 2000, Illumina Genome Analyzer II, Illumina HiSeq 2000; 50 bam
EGAD00001000226 Chordoma is a rare malignant bone tumor that expresses the transcription factor T. We conducted an association study of 40 patients with chordoma and 358 ancestry-matched, unaffected individuals with replication in an independent cohort. Whole-exome and Sanger sequencing of T exons reveals a strong risk association ( allelic odds ratio (OR) = 4.9, P = 3.3x10-11, CI= 2.9-8.1) with the common (minor allelic frequency >5%) non-synonymous SNP rs2305089 in chordoma, which is exceptional in cancer genetics. Illumina Genome Analyzer II;, Illumina HiSeq 2000; 18 bam
EGAD00001001466 Chronic lymphocytic leukaemia (CLL) is a frequent and heterogeneous disease whose genetic alterations determining the clinicobiological behaviour are not fully understood. Here, we describe a comprehensive evaluation of the genomic landscape of 452 CLLs and 54 monoclonal B-lymphocytosis (MBL), a precursor disorder. This study provides an integrated portrait of the genomic landscape of CLL, identifies new recurrent mutations acting as drivers of the disease, and suggests clinical interventions which may improve the management of patients with this neoplasia. 300 bam
EGAD00001001464 Chronic lymphocytic leukaemia (CLL) is a frequent and heterogeneous disease whose genetic alterations determining the clinicobiological behaviour are not fully understood. Here, we describe a comprehensive evaluation of the genomic landscape of 452 CLLs and 54 monoclonal B-lymphocytosis (MBL), a precursor disorder. This study provides an integrated portrait of the genomic landscape of CLL, identifies new recurrent mutations acting as drivers of the disease, and suggests clinical interventions which may improve the management of patients with this neoplasia. 882 bam
EGAD00001002110 Chronic lymphocytic leukemia (CLL) is characterized by substantial clinical heterogeneity, despite relatively few genetic alterations. To provide a basis for studying epigenome deregulation in CLL, we established genome-wide chromatin accessibility maps for 88 CLL samples from 55 patients using the ATAC-seq assay, and we also performed ChIPmentation and RNA-seq profiling for ten representative samples. Based on the resulting dataset, we devised and applied a bioinformatic method that links chromatin profiles to clinical annotations. Our analysis identified sample-specific variation on top of a shared core of CLL regulatory regions. IGHV mutation status – which distinguishes the two major subtypes of CLL – was accurately predicted by the chromatin profiles, and gene regulatory networks inferred for IGHV-mutated vs. IGHV-unmutated samples identified characteristic differences between these two disease subtypes. In summary, we discovered widespread heterogeneity in the chromatin landscape of CLL, established a community resource for studying epigenome deregulation in leukemia, and demonstrated the feasibility of chromatin accessibility mapping in cancer cohorts and clinical research. Illumina HiSeq 3000; 138
EGAD00001001421 Clinical Implications of Genomic Alterations in the Tumour and Circulation of Pancreatic Cancer Patients Illumina MiSeq; 125 fastq
EGAD00010000871 CLL and normal B cell samples using 450K 226
EGAD00001000004 CLL cancer Sample Sequencing Illumina Genome Analyzer II, Illumina Genome Analyzer 5 srf
EGAD00001000013 CLL Cancer Whole Genome Sequencing Illumina Genome Analyzer II 19 srf
EGAD00010000280 CLL Expression array Affymetrix snp 6.0 4
EGAD00010000238 CLL Expression array Affymetrix GeneChip Human Genome U133 plus 2.0 64
EGAD00010000472 CLL Expression Array Affymetrix U219 219
EGAD00010000470 CLL Expression Array GPL570 20
EGAD00010000642 CLL Expression Array 144
EGAD00010000875 CLL Expression Array Affymetrix U219 1,008
EGAD00010000252 CLL Expression Arrays Affymetrix U219 137
EGAD00010000254 CLL Methylation Arrays Illumina HumanMethylation450 165
EGAD00001001256 Clonal hematopoiesis was investigated in patients with aplastic anemia using next-generation sequencing and single-nucleotide polymorphism (SNP) array-based karyotyping. Illumina HiSeq 2000; 186 bam
EGAD00001000136 CML blast phase rearrangement screen Illumina HiSeq 2000 6 bam
EGAD00001000111 CML Discovery Project Illumina Genome Analyzer II 6 bam
EGAD00010000246 Coeliac disease cases and control samples. (1958BC samples excluded) Illumina ImmunoBeadChip - Illuminus, GenoSNP 10,758
EGAD00000000055 COLO-829 is a publicly available immortal cancer cell line and COLO-829BL is a lymphoblastoid cell line derived from the same patient Illumina Genome Analyzer II 2
EGAD00010000274 Colon matched tumour samples Illumina_2.5M 74
EGAD00010000272 Colon tumour samples Illumina_2.5M 75
EGAD00001000363 Common variable immunodeficiency (CVID) is the most common form of primary immunodeficiency with an estimated incidence of 1:10,000. It has been apparent for many years that CVID has a genetic component, occurs frequently in families and can have both a recessive or dominant mode of inheritance. In recent years, 4 genes underlying CVID have been identified; however, mutations within in them are estimated to account for no more than 10% of all cases of CVID. We have identified a multi-generational family with autosomal dominant CVID. Genome-wide linkage analysis has mapped the locus underlying CVID in this family to an approximately 9.2 Mb interval on chromosome 3q27.3-q29, between the markers D3S3570 and D3S1265. This locus is distinct from any of the previously mapped susceptibility loci suggesting a novel genetic variant is responsible for disease in this family. The aim of this study is to use exome sequencing of affected (n = 4) and unaffected (n = 4) individuals, in tandem with the available genetic mapping data, to identify the causal variant underlying CVID in this family. Illumina HiSeq 2000; 8 bam
EGAD00001002069 Complete genomics data for VCaP and PC346c. 2
EGAD00001000702 Complete set of bam files associated with study EGAS00001000622 190 bam
EGAD00001000877 Complete WGS and RNA-Seq dataset for Australian ICGC ovarian cancer sequencing project 2014-07-07, representing 93 donors. Sequencing was performed on Illumina HiSeq. Alignment of the lane-level fastq data was performed with bwa (WGS data) and RSEM (transcriptome data). For this dataset lane-level .bam files have been merged and de-duplicated to create a single bam file for each sample type (tumour/normal) for each donor. This dataset supersedes all previous datasets for this study. 310 bam
EGAD00001002228 Congenital anosmias can be complete (the lack of a sense of smell) or specific (the inability to detect specific smells). Here we obtained genomic DNA from families with multiple individuals with anosmia, suggesting they are congenital. These include those inherited in a manner consistent with dominant and recessive alleles. We have sequenced the exomes of both affected and unaffected family members on the Illumina platform. Illumina HiSeq 2000; 24
EGAD00001002210 Congenital anosmias can be complete (the lack of a sense of smell) or specific (the inability to detect specific smells). To date, only a single recessive gene underlying complete anosmia has been identified. Here we sequenced the exomes of 10 individuals from a single family, including three with complete anosmia, across three generations to identify the genetic basis of congenital anosmia in this family. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ Illumina HiSeq 2000; 10
EGAD00010000654 Control samples using SNP 6.0 Arrays 10
EGAD00010000504 Control samples using SNP Array 6.0 Affymetrix_U133plus2- 35
EGAD00010000620 Controls 3,683
EGAD00010000458 Controls using 450K DNA methylation 151
EGAD00010000494 Controls_Human660W-Quad_v1_A Illumina_Human660W-Quad_v1_A-Not supplied 4
EGAD00000000017 Cord blood control samples from Gambia 0
EGAD00001000605 CR products were obtained from each target loci using genomic DNA from human iPS cells. Subsequently, PCR products are pooled and subjected to Illumina library preparation. The library will be sequenced either by HiSeq or MiSeq. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ Illumina MiSeq;, Illumina HiSeq 2000; 10 bam
EGAD00001000076 CRLF2 sequencing project Illumina HiSeq 2000 13 bam
EGAD00001000077 CRLF2 sequencing project Exomes Illumina HiSeq 2000 26 bam
EGAD00010000542 Cusihg's syndrome normal samples using 250K Affymetrix 250K Nsp-GTYPE 16
EGAD00010000544 Cusihg's syndrome tumor samples using 250K Affymetrix 250K Nsp-GTYPE 16
EGAD00001000654 DATA FILES FOR BALL-PAX5 Illumina HiSeq 2000; 153 bam
EGAD00001001352 Data files for CONSERTING (WGS) Illumina HiSeq 2000; 38 bam
EGAD00001000657 DATA FILES FOR Histone Capture bams Illumina HiSeq 2000; 962 bam
EGAD00001000655 DATA FILES FOR Histone-NSD2_RNASeq Illumina HiSeq 2000; 8 bam
EGAD00001001418 DATA FILES FOR PCGP Dyer_iPSC 5hmc Illumina HiSeq 2000; 8 bam
EGAD00001001419 DATA FILES FOR PCGP Dyer_iPSC ChIP-Seq Illumina HiSeq 2000; 1
EGAD00001001414 DATA FILES FOR PCGP Dyer_iPSC RNASEQ Illumina HiSeq 2000; 1
EGAD00001001416 DATA FILES FOR PCGP Dyer_iPSC TEBS Illumina HiSeq 2000; 18 bam
EGAD00001001415 DATA FILES FOR PCGP Dyer_iPSC WGS Illumina HiSeq 2000; 2 bam
EGAD00001001864 DATA FILES FOR PCGP MB WGS - Supersedes (EGAD00001000269) Illumina HiSeq 2000; 76 bam
EGAD00001001248 DATA FILES FOR PCGP SJETP WXS Illumina HiSeq 2000; 13 bam
EGAD00001001245 DATA FILES FOR PCGP SJINF WES Illumina HiSeq 2000; 40 bam
EGAD00001001247 DATA FILES FOR PCGP SJMEL RNASEQ Illumina HiSeq 2000; 7 bam
EGAD00001001246 DATA FILES FOR PCGP SJMEL WXS Illumina HiSeq 2000; 28 bam
EGAD00001001054 DATA FILES FOR Ph-likeALL WES Illumina HiSeq 2000; 23 bam
EGAD00001000160 DATA FILES FOR SJACT Illumina HiSeq 2000 16 bam
EGAD00001000259 DATA FILES FOR SJAMLM7 Illumina HiSeq 2000; 8 bam
EGAD00001000268 DATA FILES FOR SJCBF Illumina HiSeq 2000; 34 bam
EGAD00001000162 DATA FILES FOR SJEPD Illumina HiSeq 2000 44 bam
EGAD00001000853 DATA FILES FOR SJEPD Illumina HiSeq 2000; 37 bam
EGAD00001000854 DATA FILES FOR SJEPD Illumina HiSeq 2000; 77 bam
EGAD00001001020 DATA FILES FOR SJEWS-WGS Illumina HiSeq 2000; 38 bam
EGAD00001000793 DATA FILES FOR SJHGG Illumina HiSeq 2000; 75 bam
EGAD00001000165 DATA FILES FOR SJINF Illumina HiSeq 2000 46 bam
EGAD00001001098 DATA FILES FOR SJINF RNASeq Illumina HiSeq 2000; 63 bam
EGAD00001000352 DATA FILES FOR SJLGG Illumina HiSeq 2000; 7 bam
EGAD00001000353 DATA FILES FOR SJLGG Illumina HiSeq 2000; 45 bam
EGAD00001000161 DATA FILES FOR SJLGG Illumina HiSeq 2000 33 bam
EGAD00001000695 DATA FILES FOR SJLGG Illumina HiSeq 2000; 46 bam
EGAD00001000878 DATA FILES FOR SJLGG Illumina HiSeq 2000; 42 bam
EGAD00001001032 DATA FILES FOR SJMEL-WGS Illumina HiSeq 2000; 12 bam
EGAD00001000159 DATA FILES FOR SJOS Illumina HiSeq 2000 37 bam
EGAD00001001053 DATA FILES FOR SJOS-WGS-2ndBatch Illumina HiSeq 2000; 27 bam
EGAD00001000163 DATA FILES FOR SJPHALL Illumina HiSeq 2000 18 bam
EGAD00001001016 DATA FILES FOR SJPhLike-RNASeq Illumina HiSeq 2000; 125 bam
EGAD00001001045 DATA FILES FOR SJRB Illumina HiSeq 2000; 20 bam
EGAD00001000164 DATA FILES FOR SJRHB Illumina HiSeq 2000, Illumina HiSeq 2000; 29 bam
EGAD00001001059 DATA FILES FOR SJRHB-WES Illumina HiSeq 2000; 56 bam
EGAD00001001052 DATA FILES FOR SJTALL Illumina HiSeq 2000; 24 bam
EGAD00001002201 Data for paper: Epigenetic dynamics of monocyte to macrophage differentiation with Chip Seq, NOMe, mRNA, total RNA, noncoding RNA, whole genome bisulfite seq, Illumina HiSeq 2000; 8
EGAD00001001668 Data from the paper Context-specific Effects of TGFβ/SMAD3 in Cancer Are Modulated by the Epigenome. Tufegdzic et al, Cell Reports 2015 Illumina HiSeq 2500; 12 bam
EGAD00001001667 Data from the paper Context-specific Effects of TGFβ/SMAD3 in Cancer Are Modulated by the Epigenome. Tufegdzic et al, Cell Reports 2015 Illumina MiSeq; 12 bam
EGAD00001001669 Data from the paper Context-specific Effects of TGFβ/SMAD3 in Cancer Are Modulated by the Epigenome. Tufegdzic et al, Cell Reports 2015 Illumina HiSeq 2500; 42 bam
EGAD00001001345 Data from the study of subclonal metastatic expansion in prostate cancer. RNA-seq of twelve samples, tumour and benign tissue, from the four initial patients. Illumina HiSeq 2000; 12 fastq
EGAD00001001343 Data from the study of subclonal metastatic expansion in prostate cancer. Whole genome shotgun sequencing of fifteen samples, tumour and whole blood, from the four initial patients. Illumina HiSeq 2000; 15 fastq
EGAD00001001344 Data from the study of subclonal metastatic expansion in prostate cancer. Whole genome shotgun sequencing of six samples, tumour and whole blood, from the three additional patients whose somatic variants were examined in depth. Illumina HiSeq 2000; 6 fastq
EGAD00001001399 Data represent genome-wide DNA methylation profiles obtained by MethylCap-seq (Diagenode’s MethylCap-kit based purification followed by Illumina GAIIx sequencing), for 70 brain tissue samples, including 65 glioblastoma samples and 5 non-tumoral tissues (obtained from epilepsy surgery). Illumina Genome Analyzer IIx; 70 fastq
EGAD00001000275 Data set for Whole-genome-Sequencing of adult medulloblastoma Illumina HiSeq 2000; 10 bam
EGAD00001000745 Data supporting the paper Transcriptional diversity during lineage commitment of human blood progenitors Illumina HiSeq 2000; 26 bam,phenotype_file,readme_file
EGAD00001001359 Dataset contains Exome-seq and RNA-seq from 2 GBM patients, as well as RNA-seq from the derived cultured cells (GNS). 6 bam
EGAD00001000777 Dataset contains MeDIP-Seq, MRE-Seq and H3K4me3 ChIP-Seq data on 5 GBM patients. 16 bam
EGAD00001001305 Dataset contains WES data from 3 astrocytoma patients: blood as control, primary tumor and recurrent tumor 9 bam
EGAD00001002133 Dataset contains Whole Exome Sequencing(WES) data from 37 individuals as aligned bam-files. The reads have been aligned using bowtie2 to human genome hg19 build. Illumina HiSeq 2000; 37
EGAD00001000758 dataset for BGI bladder cancer project Illumina Genome Analyzer II; 198 fastq
EGAD00001000760 dataset for esophageal cancer, 17pairs for whole-genome sequencing and 71pairs for whole-exome sequencing Illumina HiSeq 2000; 176 fastq
EGAD00001001006 Dataset for whole exome sequencing of 113 pairs of tumor and normal DNA samples along with 8 cell lines. Illumina HiSeq 2000; 234 fastq
EGAD00001000810 Dataset for whole exome sequencing of 49 tumor-blood pairs and transcriptome sequencing of 44 tumors for adrenocortical tumors Illumina HiSeq 2000; 106 fastq
EGAD00001000709 Dataset of CageKid Blood DNA samples 95 bam
EGAD00001000719 Dataset of CageKid Normal RNA samples 45 bam
EGAD00001000717 Dataset of CageKid Tumor DNA samples 95 bam
EGAD00001000718 Dataset of CageKid Tumor RNA samples 91 bam
EGAD00001000720 Dataset of CageKid tumor-normal paired RNA samples 90 bam
EGAD00001000176 DATA_SET_Comparing_sequencing_four_proto-typical_Burkitt_lymphomas_BL_IG-MYC_translocation Illumina HiSeq 2000;, Illumina Genome Analyzer IIx; 8 bam
EGAD00001000174 DATA_SET_Coverage_bias_sensitivity_of_variant_calling_for_4_WG_seq_tech Complete Genomics;, unspecified; 4 bam
EGAD00001000270 DATA_SET_EOP-PCA-LargeAndSmallTumors1 Illumina HiSeq 2000; 18 bam
EGAD00001000122 DATA_SET_ICGC_PedBrainTumor_Medulloblastoma Illumina HiSeq 2000, Illumina Genome Analyzer IIx 206 bam
EGAD00001000274 DATA_SET_TRANSCIPTOME_Comparing_sequencing_four_proto-typical_Burkitt_lymphomas_BL_IG-MYC_translocation Illumina HiSeq 2000; 4 bam
EGAD00010000096 DBA case samples using 250K Nsp Affymetrix_250K(Nsp) - gtype 27
EGAD00001001114 DDD DATAFREEZE 2013-12-18: 1133 trios - exome sequence BAM files (Ref: DDD Nature 2015) 3,335 bam,tab
EGAD00001001413 DDD DATAFREEZE 2013-12-18: 1133 trios - README, family trios, phenotypes, validated DNMs (Ref: DDD Nature 2015) 3,335 readme_file,tab
EGAD00001001355 DDD DATAFREEZE 2013-12-18: 1133 trios - VCF files (Ref: DDD Nature 2015) 3,335 readme_file,tab,vcf
EGAD00001001848 DDD DATAFREEZE 2014-11-04: 4293 trios - VCF files 12,539 vcf
EGAD00001000251 De novo mutations in schizophrenia Illumina HiSeq 2000; 611 bam
EGAD00001001214 Deep (>25x mean coverage) whole genome sequencing on 5-10 families drawn from the Scottish Family Health Study with four or more children. Illumina HiSeq 2000; 19 bam
EGAD00001000258 Deep RNA sequencing in CLL Illumina Genome Analyzer II; 107 fastq
EGAD00001001870 Deep sequencing of 151 cancer genes in 6 synchronous CRC of 3 patients Illumina MiSeq; 6 bam
EGAD00001000220 Deep sequencing of CTCs 454 GS FLX Titanium;, Illumina MiSeq; 3 bam
EGAD00001000225 Deep sequencing of KRAS 454 GS FLX Titanium; 8 fastq
EGAD00001001445 Deep sequencing of melanoma for driver mutations Illumina MiSeq; 3 cram
EGAD00001001123 Deep sequencing of two skin biopsies to study the landscape of somatic mutations in human adult tissues. Illumina HiSeq 2000; 2 cram
EGAD00001001441 Despite the established role of the transcription factor MYC in cancer, little is known about the impact of a new class of transcriptional regulators, the long non-coding RNAs (lncRNAs), on the way MYC is able to influence cellular transcriptome. To this aim we have intersected RNA-sequencing data from two MYC-inducible cell lines and from a cohort of 91 mature B-cell lymphomas carrying, or not carrying, genetic variants resulting in MYC over-expression. By this approach, we identified 13 lncRNAs differentially expressed in IG-MYC-positive Burkitt lymphoma and regulated in the same direction by MYC in the model cell lines. Among them we focused on a lncRNA that we named MINCR, for MYC-Induced long Non-Coding RNA, showing a strong correlation with MYC expression in MYC-positive lymphomas and also in pancreatic ductal adenocarcinomas. To understand its cellular role we performed RNA interference (RNAi) experiments and found that MINCR knock-down is associated with a reduction in cellular viability, due to an impairment in cell cycle progression. Differential gene expression analysis following RNAi showed a strongly significant enrichment of cell cycle genes among the genes down-regulate following MINCR knock-down. Interestingly these genes are enriched in MYC binding sites in their promoters, suggesting that MINCR acts as a modulator of MYC transcriptional program. Accordingly, following MINCR knock-down, we observed a reduction in the binding of MYC to the promoters of selected cell cycle genes. Finally we provide evidences that down-regulation of AURKA, AURKB and CTD1 may explain the reduction in cellular proliferation observed upon MINCR knock-down. We therefore suggest that MINCR is a newly identified player in the MYC transcriptional network able to control the expression of cell cycle genes. Illumina HiSeq 2000;, Illumina HiSeq 2500; 49 fastq
EGAD00001002229 Detection of BAP1 mutations in DNA from uveal melanoma and mesothelioma samples. Illumina HiSeq 2000; 22
EGAD00001000025 Determination of the molecular nature of the Vel blood group by exome sequencing Illumina Genome Analyzer II 4 srf
EGAD00001001332 Development of a method for separation and parallel sequencing of the genomes and transcriptomes of single cells. Illumina MiSeq;, HiSeq X Ten;, Illumina HiSeq 2500; 700 bam,cram
EGAD00010000881 Digital images of ovarian cancer sections Aperio 91
EGAD00001000200 Dilgom Exome Illumina HiSeq 2000; 130 bam
EGAD00001002148 Directed differentiation of stem cells offers a scalable solution to the need for human cell models recapitulating islet biology and T2D pathogenesis. We profiled mRNA expression at six stages of an induced pluripotent stem cell (iPSC) model of endocrine pancreas development from two donors, and characterized the distinct transcriptomic profiles associated with each stage. Established regulators of endodermal lineage commitment, such as SOX17 (log2 fold change [FC] compared to iPSCs=14.2, p-value=4.9x10-5) and the pancreatic agenesis gene GATA6 (log2 FC=12.1, p-value=8.6x10-5), showed transcriptional variation consistent with their known developmental roles. However, these analyses highlighted many other genes with stage-specific expression patterns, some of which may be novel drivers or markers of islet development. For example, the leptin receptor gene, LEPR, was most highly expressed in published data from in vivo-matured cells compared to the endocrine pancreas-like cells (log2 FC=5.5, p-value=2.0x10-12), suggesting a role for the leptin pathway in the maturation process. Endocrine pancreas-like cells showed significant stage-selective expression of adult islet genes, including INS, ABCC8, and GLP1R, and enrichment of relevant GO-terms (e.g. “insulin secretion”; odds ratio=4.2, p-value=1.9x10-3): however, principal component analysis indicated that in vitro-differentiated cells were more immature than adult islets. Integration of the stage-specific expression information with genetic data from T2D genome-wide association studies revealed that 46 of 82 T2D-associated loci harbor genes present in at least one developmental stage, facilitating refinement of potential effector transcripts. Together, these data show that expression profiling in an iPSC islet development model can further understanding of islet biology and T2D pathogenesis. Illumina HiSeq 2000; 12
EGAD00001000707 Discovery of resistance mechanisms to the BRAF inhibitor vemurafenib in metastatic BRAF mutant melanoma by massively-parallel sequencing of tumour samples. Comparison of genomic characteristics of pretreatment 'sensitive' to recurrence 'resistant' tumours to identify the genetics of drug resistance. Illumina HiSeq 2000; 57 cram
EGAD00001000946 Divergent clonal selection dominates medulloblastoma at recurrence 125 bam
EGAD00010000658 DLBCL 148 SNP 6.0 Cohort 148
EGAD00001001028 DNA belonging to 16 tumour/normal samples were treated with bisulfite, then up to 5 different bisulfite PCRs were performed in each one of the samples. Amplicons form the same sample were pooled and submitted to sequencing on a MiSeq platform. Illumina MiSeq; 18 cram
EGAD00001001017 DNA extracted from multiple biopsies taken from different areas of primary lung tumours will be subjected to targeted re-sequencing and analysed in order to assess intra-tumour heterogeneity with respect to mutations in a selection of cancer related genes. Illumina HiSeq 2000; 31 bam,cram
EGAD00001001938 DNA from each sample (100ng) was sheared on Covaris S220 (Covaris): duty cycle - 10%, intensity -5.0, bursts per sec - 200, duration - 300 sec, mode - frequency sweeping, power - 23V, temperature -5:5 ?C to 6 ?C, water level - 13. Libraries were prepared with the TruSeq Nano DNA LT Sample Prep Kit (Illumina) using a modi?ed protocol - Sample Puri?cation Beads were replaced by Agencourt AMPure XP beads (Beckman Coultier) and size selection after the End Repair was done to remove only the short fragments. Quality and quantity for contructed libraries were assessed with DNA 7500 kit on Agilent 2100 Bioanalyzer and with Kapa Quanti?cation kit (KAPA Biosystems) on 7900HT Fast Real-Time PCR System (Applied Biosystems) according to the supplier's recommendations, respectively. Libraries from 18 barcoded samples were pooled together in equimolar amounts and each pool was loaded on a single lane of a HiSeq Single End Flowcell (Illumina), followed by cluster generation on a cBot (Illumina) and sequencing on a HiSeq 2500 (Illumina) in a single-read 50bp mode. Reads were aligned using bwa-mem v0.7.12-r1039 [10] to the 1000 genomes version of human genome build GRCh37. Picard (http://picard.sourceforge.net) was used to remove duplicate reads. Illumina HiSeq 2500; 60 bam
EGAD00010000379 DNA methylation analysis of 2 peripheral blood samples HumanMethylation450k Bead Chip - Genome Studio 2
EGAD00010000646 DNA methylation analysis of 35 prostate tumor and 6 normal prostate samples 41
EGAD00010000427 DNA methylation analysis of 4 peripheral blood samples HumanMethylation450k Bead Chip - Genome Studio 4
EGAD00010000429 DNA methylation analysis of 4 primary lymphoma samples HumanMethylation450k Bead Chip - Genome Studio 4
EGAD00010000377 DNA methylation analysis of 6 primary lymphoma samples HumanMethylation450k Bead Chip - Genome Studio 6
EGAD00010000604 DNA methylation data using Illumina 450K 2,195
EGAD00001000394 DNA methylation has been shown to play a major role in determining cellular phenotype by regulating gene expression. Moreover, dysregulation of differentially methylated genes has been implicated in disease pathogenesis of various conditions including cancer development as well as autoimmune diseases such as systemic Lupus erythematosus and rheumatoid arthritis. Evidence is rapidly accumulating for a role of DNA methylation in regulating immune responses in health and disease. However, the exact mechanisms remain unknown. The overall aim of the project is to investigate the role of epigenetic mechanisms in regulating immunity and their impact on autoimmune disease pathogenesis. The aim of this pilot study is to perform whole genome methylation analysis in peripheral blood mononuclear cells (PBMCs) and cell subsets (CD4, CD8, CD14, CD19, CD16 and whole PBMCs) obtained from 6 healthy volunteers. Whole genome methylation analysis will be performed using two methodological approaches, the Infinium Methylation Bead Array K450 (Illumina) and MeDIP-seq. mRNA expression arrays will also be performed in order to correlate DNA methylation with gene expression as well as genotyping on the Illumina OmniExpress chip Illumina Genome Analyzer II; 6 bam
EGAD00010000870 DNA methylation microarray Illumina_Infinium_HumanMethylation450 48
EGAD00001000952 DNA methylation profiling of 8 control samples from adult (4) and fetal brain (4) Illumina HiSeq 2000; 8 fastq
EGAD00001000641 DNA replication errors occurring in mismatch repair (MMR) deficient cells persist as mismatch mutations and predispose to a range of tumors. Here, we sequenced the first whole-genomes from MMR-deficient endometrial tumors. Complete Genomics;, Illumina HiSeq 2000; 44 CompleteGenomics_native,bam
EGAD00001001900 DNA sequencing reads of human adult stem cell cultures from liver, colon and small intestine. Including biopsy or blood samples of the donors. HiSeq X Ten;, Illumina HiSeq 2500; 55 bam
EGAD00001001252 DNA was derived from the primary tumour, lung metastasis, and peri-aortic lymph node metastasis. DNA from the spleen was used as a normal control. For WE sequencing we user Hybrid capture (Nimblegen version 3.0) of the lymph node and lung metastases, primary tumour and spleen normal; we generated ~100-fold coverage. 4 bam
EGAD00001001253 DNA was derived from the primary tumour, lung metastasis, and peri-aortic lymph node metastasis. DNA from the spleen was used as a normal control. WG sequencing produced ~30-fold (primary tumour, spleen normal)-50-fold (lung metastasis) coverage 3 bam
EGAD00001001549 DNase-Hypersensitivity data for 1 Acute Myeloid Leukemia sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_dnaseseq_analysis_20150820 Illumina HiSeq 2000; 1 fastq
EGAD00001001190 DNase-Hypersensitivity data for 1 Acute myeloid leukemia sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_dnaseseq_analysis_20140811 Illumina HiSeq 2000; 1 fastq
EGAD00001001545 DNase-Hypersensitivity data for 1 alternatively activated macrophage sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_dnaseseq_analysis_20150820 Illumina HiSeq 2000; 1 fastq
EGAD00001001524 DNase-Hypersensitivity data for 1 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_dnaseseq_analysis_20150820 Illumina HiSeq 2000; 1 fastq
EGAD00001000942 DNase-Hypersensitivity data for 1 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_dnaseseq_analysis_20140811 Illumina HiSeq 2000; 1 fastq
EGAD00001001161 DNase-Hypersensitivity data for 1 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_dnaseseq_analysis_20140811 Illumina HiSeq 2000; 1 fastq
EGAD00001001475 DNase-Hypersensitivity data for 1 CD8-positive, alpha-beta T cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_dnaseseq_analysis_20150820 Illumina HiSeq 2000; 1 fastq
EGAD00001000931 DNase-Hypersensitivity data for 1 macrophage sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_dnaseseq_analysis_20140811 Illumina HiSeq 2000; 1 fastq
EGAD00001001198 DNase-Hypersensitivity data for 14 macrophage sample(s). 18 run(s), 14 experiment(s), 14 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_dnaseseq_analysis_20140811 Illumina HiSeq 2000; 14 fastq
EGAD00001001581 DNase-Hypersensitivity data for 16 macrophage sample(s). 20 run(s), 16 experiment(s), 16 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_dnaseseq_analysis_20150820 Illumina HiSeq 2000; 16 fastq
EGAD00001000926 DNase-Hypersensitivity data for 2 inflammatory macrophage sample(s). 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_dnaseseq_analysis_20140811 Illumina HiSeq 2000; 2 fastq
EGAD00001001193 DNase-Hypersensitivity data for 2 inflammatory macrophage sample(s). 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_dnaseseq_analysis_20140811 Illumina HiSeq 2000; 2 fastq
EGAD00001001560 DNase-Hypersensitivity data for 2 monocyte sample(s). 4 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_dnaseseq_analysis_20150820 Illumina HiSeq 2000; 2 fastq
EGAD00001001185 DNase-Hypersensitivity data for 2 monocyte sample(s). 4 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_dnaseseq_analysis_20140811 Illumina HiSeq 2000; 2 fastq
EGAD00001001573 DNase-Hypersensitivity data for 3 inflammatory macrophage sample(s). 3 run(s), 3 experiment(s), 3 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_dnaseseq_analysis_20150820 3 fastq
EGAD00001001476 DNase-Hypersensitivity data for 4 CD14-positive, CD16-negative classical monocyte sample(s). 4 run(s), 4 experiment(s), 4 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_dnaseseq_analysis_20150820 Illumina HiSeq 2000; 4 fastq
EGAD00001000905 DNase-Hypersensitivity data for 5 CD14-positive, CD16-negative classical monocyte sample(s). 5 run(s), 5 experiment(s), 5 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_dnaseseq_analysis_20140811 Illumina HiSeq 2000; 5 fastq
EGAD00001001130 DNase-Hypersensitivity data for 5 CD14-positive, CD16-negative classical monocyte sample(s). 5 run(s), 5 experiment(s), 5 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_dnaseseq_analysis_20140811 Illumina HiSeq 2000; 5 fastq
EGAD00001000674 DNaseI-seq for monocytes Illumina HiSeq 2000; 4 fastq
EGAD00010000466 Down syndrome CNV genotyping data NimbleGen 135K aCGH - NimbleScan 108
EGAD00010000464 Down syndrome SNP genotyping data Illumina 550K - Illumina Genome Studio 338
EGAD00001001066 Dynamics of genomic clones in breast cancer patient xenografts at single cell resolution Illumina MiSeq;, Illumina HiSeq 2000; 188 bam
EGAD00001000227 EGAD00001000227_UK10K_NEURO_ABERDEEN_REL_2012_07_05 Illumina HiSeq 2000; 347 vcf
EGAD00001000228 EGAD00001000228_UK10K_NEURO_ASD_BIONED_REL_2012_07_05 Illumina HiSeq 2000; 59 vcf
EGAD00001000229 EGAD00001000229_UK10K_NEURO_ASD_FI_REL_2012_07_05 Illumina HiSeq 2000; 85 vcf
EGAD00001000230 EGAD00001000230_UK10K_NEURO_ASD_GALLAGHER_REL_2012_07_05 Illumina HiSeq 2000; 72 vcf
EGAD00001000231 EGAD00001000231_UK10K_NEURO_ASD_SKUSE_REL_2012_07_05 Illumina HiSeq 2000; 320 vcf
EGAD00001000232 EGAD00001000232_UK10K_NEURO_ASD_TAMPERE_REL_2012_07_05 Illumina HiSeq 2000; 54 vcf
EGAD00001000233 EGAD00001000233_UK10K_NEURO_EDINBURGH_REL_2012_07_05 Illumina HiSeq 2000; 219 vcf
EGAD00001000234 EGAD00001000234_UK10K_NEURO_FSZNK_REL_2012_07_05 Illumina HiSeq 2000; 281 vcf
EGAD00001000235 EGAD00001000235_UK10K_NEURO_IOP_COLLIER_REL_2012_07_05 Illumina HiSeq 2000; 170 vcf
EGAD00001000236 EGAD00001000236_UK10K_NEURO_MUIR_REL_2012_07_05 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 167 vcf
EGAD00001000237 EGAD00001000237_UK10K_NEURO_GURLING_REL_2012_07_05 Illumina HiSeq 2000; 43 vcf
EGAD00001000239 EGAD00001000239_UK10K_NEURO_IMGSAC_REL_2012_07_05 Illumina HiSeq 2000; 114 vcf
EGAD00001000241 EGAD00001000241_UK10K_OBESITY_SCOOP_REL_2012_07_05 Illumina HiSeq 2000; 674 vcf
EGAD00001000242 EGAD00001000242_UK10K_NEURO_ASD_MGAS_REL_2012_07_05 Illumina HiSeq 2000; 60 vcf
EGAD00010000674 ELSA genome-wide genotypes, excluding estimated related individuals. There are 3 files: .fam, .bim, .bed 7,412
EGAD00010000676 ELSA genome-wide genotypes, including estimated related individuals. There are 3 files: .fam, .bim, .bed 7,452
EGAD00001000224 Enrichment of CRC 454 GS FLX Titanium; 2 bam
EGAD00001002220 Enteropathy-associated T-cell lymphoma (EATL), a rare and aggressive intestinal malignancy of intraepithelial T lymphocytes, comprises two disease variants (EATL-I and EATL-II) differing in clinical characteristics and pathological features. Here we report findings derived from whole exome sequencing of 15 EATL-II tumor-normal tissue pairs. 15
EGAD00010000787 Epigen-Brasil samples using HumanOmni2.5 6,487
EGAD00000000027 eQTL data for European newborns Ilumina HumanHap550-2v3_B-Beadstudio 176
EGAD00001000088 ER-, HER2-, PR- breast Cancer genome sequencing Illumina Genome Analyzer II 6 bam
EGAD00001001691 Esophageal cancer is one of the most aggressive cancers and the sixth leading cause of cancer death worldwide1. Approximately 70% of the global esophageal cancers occur in China and over 90% histopathological forms of this disease are esophageal squamous cell carcinoma (ESCC)2-3. Currently, there are limited clinical approaches for early diagnosis and treatment for ESCC, resulting in a 10% 5-year survival rate for the patients. Meanwhile, the full repertoire of genomic events leading to the pathogenesis of ESCC remains unclear. Here we show a comprehensive genomic analysis in 158 ESCC cases, as part of the International Cancer Genome Consortium (ICGC) Research Projects (http://icgc.org/icgc/cgp/72/371/1001734). We conducted whole-genome sequencing in 14 ESCC cases and whole-exome sequencing in 90 cases. Illumina HiSeq 2000; 208 fastq
EGAD00001000129 Essential Thrombocythemia Myeloproliferative Disease exome sequencing Illumina HiSeq 2000, Illumina HiSeq 2000; 189 bam
EGAD00001000252 Evaluation of PCR library method on whole genome samples Illumina HiSeq 2000; 12 bam
EGAD00001002108 Exome and targeted amplicon sequencing data for tumor, germline and plasma samples from a patient with metastatic breast cancer. Illumina MiSeq; 30
EGAD00001001269 Exome bam files of 75 Individuals From Multiply Affected Coeliac Families Illumina Genome Analyzer II;, Illumina Genome Analyzer IIx; 75 bam
EGAD00001000216 Exome capture sequencing of colon tumor/normal pairs Illumina HiSeq 2000; 144 fastq
EGAD00001000222 Exome capture sequencing of SCLC tumor/normal pairs and cell lines Illumina HiSeq 2000; 103 fastq
EGAD00001001863 Exome data of PDX models. Illumina HiSeq 2500; 4 fastq
EGAD00001002164 Exome from EGA00001001848 Illumina HiSeq 2000; 2
EGAD00001000885 Exome read sequences for 30 tumor-normal pairs for the study "Diverse modes of genomic alterations in Hepatocellular Carcinoma". Illumina HiSeq 2000; 60 fastq
EGAD00001002160 Exome Seq for EGAS00001001845 Illumina HiSeq 2500; 2
EGAD00001002159 Exome Seq for Study EGAS00001001844 Illumina HiSeq 2000; 2
EGAD00001002162 Exome Seq from EGAS00001001846 Illumina HiSeq 2500; 2
EGAD00001001316 Exome sequence analysis of individuals with severe early onset inflammatory bowel disease, and their families. Individuals are ascertained through the COLORS in IBD study, which includes centres throughout UK and Europe. Illumina HiSeq 2000; 138 cram
EGAD00001000058 Exome Sequencing analysis Illumina Genome Analyzer II 21 Illumina_native_qseq
EGAD00001001002 Exome sequencing data for 8 pairs of seminomas and matched normal Illumina HiSeq 2000;, Illumina Genome Analyzer IIx; 16 fastq
EGAD00001001913 Exome sequencing data for Mesothelioma Illumina HiSeq 2500; 198 fastq
EGAD00001000626 Exome sequencing data for tumor and matched normal samples of the EGAS00001000495 project. Illumina HiSeq 2000; 114 fastq
EGAD00001000001 Exome sequencing identifies frequent mutation of the SWI/SNF complex gene PBRM1 in renal carcinoma 18
EGAD00001000291 Exome sequencing identifies mutation of the ribosome in T-cell acute lymphoblastic leukemia Illumina HiSeq 2000; 128 bam
EGAD00001001385 Exome sequencing in 3 Möbius patients AB SOLiD 4 System; 3
EGAD00001000053 Exome sequencing in patients with Calcific Aortic Valve Stenosis Illumina HiSeq 2000 20 bam
EGAD00001000022 Exome sequencing in patients with cardiac arrhythmias Illumina Genome Analyzer II 20 srf
EGAD00001000345 Exome sequencing of 12 DNA samples obtained from patients with structural brain malformations. Illumina HiSeq 2000; 9 bam
EGAD00001001021 Exome sequencing of 1000 samples from the UK 1958 Birth Cohort. DNA library preps prepared with Illumina TruSeq sample preparation kit. The captured DNA libraries were PCR amplified using the supplied paired-end PCR primers. Sequencing was performed with an Illumina HiSeq2000 (SBS Kit v3, one pool per lane) generating 2x101-bp reads. Illumina HiSeq 2500; 1,000 fastq
EGAD00001001462 Exome sequencing of 142 samples with corresponding Sanger sequencing results for 409 variants and 321 negative sites. DNA library preps prepared with Illumina TruSeq sample preparation kit. The captured DNA libraries were PCR amplified using the supplied paired-end PCR primers. Sequencing was performed with an Illumina HiSeq2000 (SBS Kit v3, one pool per lane) generating 2x101-bp reads. Illumina HiSeq 2000;, Illumina HiSeq 2500; 142
EGAD00001001973 Exome sequencing of 184 samples from consanguineous families with different congenital heart defects collected at KAIMRC, Riyadh, Saudi Arabia. Illumina HiSeq 2000;, Illumina HiSeq 2500; 179 cram
EGAD00001000344 Exome sequencing of 30 parent-offspring trios to >50X mean depth, where the offspring has sporadic TOF, to identify potential causal de novo mutations. We will use the exome plus design for pulldown that incorporates ~6.8Mb of additional regulatory sequences in addition to the ~50Mb GENCODE exome. Illumina HiSeq 2000; 90 bam
EGAD00001002185 Exome sequencing of 32 patient samples from Sri Lanka with the condition haemoglobin E beta thalassaemia Illumina HiSeq 2000; 32
EGAD00001001347 Exome sequencing of a case of lethal EBV-driven LPD Illumina HiSeq 2000; 3 cram
EGAD00001000348 Exome sequencing of Bilateral Anophthalmia cases- Pilot Study Illumina Genome Analyzer II; 16 bam
EGAD00001000791 Exome sequencing of familial and sporadic small cell cancer of ovary cases. Illumina HiSeq 2000;, Illumina HiSeq 2500; 16 fastq
EGAD00001002251 Exome sequencing of families with Congenital Heart Defects of diverse sub-phenotypes. Comprises both parent-offspring trios for sporadic cases and multiplex families. Collaboration with David Brook, University of Nottingham. Funded by the British Heart Foundation. Illumina HiSeq 2000; 646
EGAD00001002009 Exome sequencing of high-risk prostate cancer Illumina HiSeq 2000; 78
EGAD00001000015 Exome sequencing of hyperplastic polyposis patients. Illumina HiSeq 2000, Illumina Genome Analyzer II, Illumina HiSeq 2000; 84 bam,srf
EGAD00001001003 Exome sequencing of lymphocyte DNA from 12 affected individuals from six unrelated, non-syndromic Wilms tumor families. Illumina HiSeq 2000; 12 fastq
EGAD00001001854 Exome sequencing of nine PCC/PGL tumors, SF and FFPE samples 18 bam
EGAD00001000346 Exome sequencing of patients and their families with diverse rare neurological disorders. Some families have prior linkage data identifying a specific chromosomal interval or interest, other families do not have linkage data available. Many of these families come from special populations whose demography or preference for consanguineous marriages make them particularly tractable for genetic studies. Illumina HiSeq 2000; 30 bam
EGAD00001001009 Exome sequencing of peripheral blood from 4 individuals of a family with familial colorectal cancer type X Illumina HiSeq 2000; 4 fastq
EGAD00001000887 Exome sequencing of Resistant BCC samples. Illumina HiSeq 2000; 23 fastq
EGAD00001002208 Exome sequencing of short SGA children with IGF-I and insulin resistance. Collaboration with Professor David Dunger, University of Cambridge. Funded by NIHR. Illumina HiSeq 2000; 15
EGAD00001000963 Exome sequencing of sporadic schwannomatosis patients 16 bam
EGAD00001001125 Exome sequencing of Untreated BCC samples. Illumina HiSeq 2000; 91 fastq
EGAD00001001887 Exome sequencing VCF files describing mutations during glioma progression. 82 vcf
EGAD00001000715 Exome sequencing was performed for paired tumor/normal samples from patients with corticotropin-independnet Cushing's syndrome. Tumor DNA was extracted from adrenocortical adenomas and normal DNA was extracted from adjacent adrenal tissues or periphral blood. Illumina HiSeq 2000; 16 bam
EGAD00001000815 Exome-seq, RNA-Seq, SNP array profiling of gastric tumor samples. Illumina HiSeq 2000; 102 fastq
EGAD00001000619 Experiments using targeted pulldown methods will be sequenced to validate findings in the exomes of patients with Myeloproliferative Neoplasms (MPN). Illumina HiSeq 2000; 360 bam
EGAD00001001238 Extension analysis to pursue candidate genes of interest in chordoma Illumina HiSeq 2000; 262 cram
EGAD00001001239 Extension analysis to pursue candidate genes of interest in chordoma Illumina HiSeq 2000; 262 cram
EGAD00001000722 Extension of angiosarcoma whole genome sequencing study Illumina HiSeq 2000; 8 cram
EGAD00001000738 Extension of angiosarcoma whole genome sequencing study Illumina HiSeq 2000; 4 cram
EGAD00001001064 Extension of angiosarcoma whole genome sequencing study Illumina MiSeq; 4 cram
EGAD00001000656 FACS phenotype of 1629 Sardinian samples 1,629 phenotype_file
EGAD00001000016 Familial Melanoma Sequencing Illumina HiSeq 2000, Illumina Genome Analyzer II, Illumina HiSeq 2000; 89
EGAD00001000128 Familial Thrombocytosis germline exome sequencing Illumina HiSeq 2000, Illumina HiSeq 2000; 4 bam
EGAD00001000072 Fanconi Anemia transformation to AML Illumina HiSeq 2000 6 bam
EGAD00001001403 Fastq data for ChIP-Seq (H3K27ac) assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium. Illumina HiSeq 2000;, Illumina HiSeq 2500; 48 fastq
EGAD00001001404 Fastq data for ChIP-Seq (H3K27me3) assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium. Illumina HiSeq 2000;, Illumina HiSeq 2500; 48 fastq
EGAD00001001405 Fastq data for ChIP-Seq (H3K36me3) assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium. Illumina HiSeq 2000;, Illumina HiSeq 2500; 48 fastq
EGAD00001001406 Fastq data for ChIP-Seq (H3K4me1) assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium. Illumina HiSeq 2000;, Illumina HiSeq 2500; 48 fastq
EGAD00001001407 Fastq data for ChIP-Seq (H3K4me3) assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium. Illumina HiSeq 2000;, Illumina HiSeq 2500; 48 fastq
EGAD00001001408 Fastq data for ChIP-Seq (H3K9me3) assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium. Illumina HiSeq 2000;, Illumina HiSeq 2500; 48 fastq
EGAD00001001409 Fastq data for ChIP-Seq (Input) assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium. Illumina HiSeq 2000;, Illumina HiSeq 2500; 48 fastq
EGAD00001001401 Fastq data for smRNA-Seq assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium. Illumina HiSeq 2000; 28 fastq
EGAD00001001402 Fastq data for stranded mRNA-Seq assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium. Illumina HiSeq 2000;, Illumina HiSeq 2500; 32 fastq
EGAD00001001312 Fastq data for whole genome bisulfite sequencing assays for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium. Illumina HiSeq 2000;, Illumina HiSeq 2500; 30 fastq
EGAD00001001400 Fastq data for whole genome shotgun sequencing assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium. Illumina HiSeq 2000;, Illumina HiSeq 2500; 27 fastq
EGAD00001001646 Fastq files corresponding to RNA-Seq dataset for PTPN1 project (EGAS00001000554) Illumina Genome Analyzer II;, Illumina HiSeq 2000;, Illumina Genome Analyzer; 10 fastq
EGAD00001000873 Fastq files of 10 samples of condrosarcoma Illumina HiSeq 2000;, Illumina Genome Analyzer IIx; 10 fastq
EGAD00001000446 Fastq files of 213 samples of hepatocellular carcinoma (NCCRI) Illumina HiSeq 2000; 213 fastq
EGAD00001001076 Fastq files of 239 samples of biliary tract cancer Illumina HiSeq 2000; 239 fastq
EGAD00001001024 Fastq files of 52 samples of hepatocellular carcinoma (RCAST, THCC) Illumina HiSeq 2000; 104 fastq
EGAD00001001030 Fastq files of 98 samples of hepatocellular carcinoma (BCM, HCC-JP) Illumina HiSeq 2000; 196 fastq
EGAD00001001693 Fastq files of RNAseq of 182 samples of biliary tract cancer Illumina HiSeq 2000; 182 fastq
EGAD00001000795 Fernandez-Cuesta et al, 2014, Nature Communication, RNA Sequencing data set Illumina HiSeq 2000; 69 fastq
EGAD00001000820 Fernandez-Cuesta et al, 2014, Nature Communication, Whole exome sequencing data set Illumina HiSeq 2000; 15 bam
EGAD00001000813 Fernandez-Cuesta et al., 2014, Nature Communication, Whole genome sequencing was performed using a read length of 2x100 bp for all samples. On average, 110 Gb of sequence were produced per sample, aiming a mean coverage of 30x for both tumour and matched normal. Illumina HiSeq 2000; 30 bam
EGAD00001000746 Fernandez-Cuesta et al., RNAseq data Pipline Illumina HiSeq 2000; 25 fastq
EGAD00001000678 FFPE CPA accreditation of genome-scale sequencing in routinely collected formalin-fixed paraffin-embedded (FFPE) cancer specimens versus matched fresh-frozen samples using targeted pulldown capture prior to Illumina sequencing. Illumina HiSeq 2000; 341 bam,cram
EGAD00001000868 FFPE CPA accreditation of genome-scale sequencing in routinely collected formalin-fixed paraffin-embedded (FFPE) cancer specimens versus matched fresh-frozen samples using targeted pulldown capture prior to Illumina sequencing. Illumina HiSeq 2000; 60 cram
EGAD00001001122 FFPE normal panel generation for use with V3 cancer panel 0618521 Illumina HiSeq 2000; 94 cram
EGAD00001000828 Fibroblasts have been shown to re-program into induced pluripotent stem (hiPS) cells, through over-expression of pluripotency genes. These hiPS cells show similar characteristics to embryonic stem cells including cell surface markers, epigenetic changes and ability to differentiate into the three germ layers. However it is unclear as to the extent of changes in gene expression through the re-programming process.. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ Illumina HiSeq 2000; 6 bam
EGAD00001000692 Files associated with the dataset: HS1626.bam, HS1484.bam, HS1483.bam, HS1482.bam, HS1481.bam, HS1480.bam, HS1479.bam, HS1478.bam, A13805.bam, A13800.bam, A13799.bam, A05253.bam, A05252.bam, A13806.bam Illumina Genome Analyzer II;, Illumina HiSeq 2000;, Illumina Genome Analyzer; 12 bam
EGAD00010000662 Finnish population cohort genotyping 7,803
EGAD00010000664 Finnish population cohort genotyping_B 340
EGAD00001001936 Firs 1106 16S rDNA data for the Flemish Gut Flora Project Illumina MiSeq; 1,106 fastq
EGAD00001000195 For information about this sample set, please contact the sample custodian Nic Timpson: N.J.Timpson@bristol.ac.uk Illumina HiSeq 2000; 740 vcf
EGAD00001000098 FRCC Exome sequencing Illumina Genome Analyzer II 16 bam
EGAD00010000887 Freeze 1 of the RP3 project Illumina Human Methylation 450k BeadChip 3,898
EGAD00010000758 French glioma case germline genotypes using Illumina HumanExome-12v1_A array Illumina HumanExome-12v1_A 906
EGAD00010000756 French glioma control germline genotypes using Illumina HumanExome-12v1_A array Illumina HumanExome-12v1_A 699
EGAD00001001351 Frequent somatic transfer of mitochondrial DNA into the nuclear genome of human cancer cells Illumina HiSeq 2000; 2 bam
EGAD00001001348 Frequent somatic transfer of mitochondrial DNA into the nuclear genome of human cancer cells Illumina HiSeq 2000; 8 bam,cram
EGAD00001001349 Frequent somatic transfer of mitochondrial DNA into the nuclear genome of human cancer cells Illumina HiSeq 2000; 4 bam
EGAD00001001350 Frequent somatic transfer of mitochondrial DNA into the nuclear genome of human cancer cells Illumina HiSeq 2000; 8 bam,cram
EGAD00001001353 Frequent somatic transfer of mitochondrial DNA into the nuclear genome of human cancer cells Illumina HiSeq 2000; 2 bam
EGAD00001000212 Functional characterisation of CpG islands in human tissues Illumina Genome Analyzer II; 26 bam
EGAD00000000110 Gabriel aggregate data from the asthma study samples Illumina 610-Quad 0
EGAD00000000073 Gabriel samples from the 1958 British Birth Cohort Illumina 610-Quad 0
EGAD00000000076 Gabriel samples from the Australian Bussleton Cohort Illumina 610-Quad 0
EGAD00000000077 Gabriel samples from the Australian Bussleton Cohort Illumina 610-Quad 0
EGAD00000000095 Gabriel samples from the Dutch PIAMA cohort Illumina 610-Quad 0
EGAD00000000096 Gabriel samples from the Dutch PIAMA cohort Illumina 610-Quad 0
EGAD00000000083 Gabriel samples from the French EGEA Cohort Illumina 610-Quad 0
EGAD00000000082 Gabriel samples from the French EGEA Cohort Illumina 610-Quad 0
EGAD00000000085 Gabriel samples from the German Gabriel Advanced Survey Illumina 610-Quad 0
EGAD00000000084 Gabriel samples from the German Gabriel Advanced Survey Illumina 610-Quad 0
EGAD00000000092 Gabriel samples from the German MAGIS cohort Illumina 610-Quad 0
EGAD00000000093 Gabriel samples from the German MAGIS cohort Illumina 610-Quad 0
EGAD00000000088 Gabriel samples from the Karelia Allergy Study Illumina 610-Quad 0
EGAD00000000089 Gabriel samples from the Karelia Allergy Study Illumina 610-Quad 0
EGAD00000000087 Gabriel samples from the multicenter GAIN cohort Illumina 610-Quad 0
EGAD00000000086 Gabriel samples from the multicenter GAIN cohort Illumina 610-Quad 0
EGAD00000000105 Gabriel samples from the multicenter occupational cohort Illumina 610-Quad 0
EGAD00000000106 Gabriel samples from the multicenter occupational cohort Illumina 610-Quad 0
EGAD00000000107 Gabriel samples from the multicenter occupational cohort Illumina 610-Quad 0
EGAD00000000090 Gabriel samples from the Russian KMSU cohort Illumina 610-Quad 0
EGAD00000000091 Gabriel samples from the Russian KMSU cohort Illumina 610-Quad 0
EGAD00000000102 Gabriel samples from the Russian TOMSK cohort Illumina 610-Quad 0
EGAD00000000101 Gabriel samples from the Russian TOMSK cohort Illumina 610-Quad 0
EGAD00000000104 Gabriel samples from the Russian UFA cohort Illumina 610-Quad 0
EGAD00000000103 Gabriel samples from the Russian UFA cohort Illumina 610-Quad 0
EGAD00000000075 Gabriel samples from the Swedish BAMSE Cohort Illumina 610-Quad 0
EGAD00000000074 Gabriel samples from the Swedish BAMSE Cohort Illumina 610-Quad 0
EGAD00000000098 Gabriel samples from the Swiss SALPADIA cohort Illumina 610-Quad 0
EGAD00000000097 Gabriel samples from the Swiss SALPADIA cohort Illumina 610-Quad 0
EGAD00000000108 Gabriel samples from the UK AUGOSA cohort Illumina 610-Quad 0
EGAD00000000094 Gabriel samples from the UK MRCA cohort Illumina 610-Quad 0
EGAD00000000109 Gabriel samples from the UK SEVERE cohort Illumina 610-Quad 0
EGAD00010000940 Gambian specimens with trachomatous scarring WHO grade C2/C3 Illiumina Omni 2.5 1,531
EGAD00010000941 Gambian specimens without trachomatous scarring Illumina Omni 2.5 1,531
EGAD00001000075 Gastric and Esophageal tumour rearrangement screen Illumina HiSeq 2000 32 bam
EGAD00001001118 Gastric Cancer (GC) is a highly heterogeneous disease. To identify potential clinically actionable therapeutic targets that may inform individualized treatment strategies, we performed whole-exome sequencing on 78 GCs of differing histologies and anatomic locations, as well as whole-genome sequencing on two GC cases, each with 3 primary tumours and 2 matching lymph node metastases. The data showed two distinct GC subtypes with either high-clonality (HiC) or low-clonality (LoC). Illumina HiSeq 2000; 168 fastq
EGAD00001000046 Gastric Cancer Exome Sequencing Illumina HiSeq 2000, Illumina Genome Analyzer IIx 43 fastq
EGAD00010000578 Gencode case samples using 550K 249
EGAD00010000580 Gencode control samples using 550K 217
EGAD00010000889 Gencode control samples using SNP6.0 SNP6.0 183
EGAD00001000003 Gencode Exome Pilot Illumina Genome Analyzer II 7 srf
EGAD00010000460 GENCORD2 DNA methylation 294
EGAD00001000425 GENCORD2 RNA-seq BAM files using BWA Illumina Genome Analyzer II;, Illumina HiSeq 2000; 568 bam
EGAD00001000198 Gene Discovery in Age-Related Hearing Loss Illumina Genome Analyzer II;, Illumina HiSeq 2000; 20 bam
EGAD00010000738 Generation Scotland APOE data 18,336
EGAD00001000131 Genetic landscape of hepatocellular carcinoma Illumina HiSeq 2000 48 bam
EGAD00001000055 Genetic variation in Kuusamo Illumina HiSeq 2000, Illumina HiSeq 2000; 434 vcf
EGAD00001002036 Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 3
EGAD00001002030 Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 3
EGAD00001002033 Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 3
EGAD00001002048 Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 3
EGAD00001002031 Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 3
EGAD00001002044 Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 3
EGAD00001002021 Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 3
EGAD00001002035 Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 3
EGAD00001002026 Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 4
EGAD00001002041 Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 3
EGAD00001002047 Genome and transcriptome sequence data from a breast ductal carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 3
EGAD00001002017 Genome and transcriptome sequence data from a breast primary patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 3
EGAD00001002019 Genome and transcriptome sequence data from a breast primary patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 2
EGAD00001001876 Genome and transcriptome sequence data from a colorectal adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study. These data are included in the manuscript entitled, "Response to Angiotensin Blockade with Irbesartan in a Patient with Metastatic Colorectal Cancer". 3 bam
EGAD00001002022 Genome and transcriptome sequence data from a colorectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 3
EGAD00001002025 Genome and transcriptome sequence data from a colorectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 3
EGAD00001002027 Genome and transcriptome sequence data from a colorectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 3
EGAD00001002046 Genome and transcriptome sequence data from a liposarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 3
EGAD00001002023 Genome and transcriptome sequence data from a lung cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 2
EGAD00001002045 Genome and transcriptome sequence data from a lung cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 2
EGAD00001002018 Genome and transcriptome sequence data from a melanoma skin cancer - squamous cell carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 3
EGAD00001002020 Genome and transcriptome sequence data from a metastatic NPC patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 2
EGAD00001002034 Genome and transcriptome sequence data from a pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 2
EGAD00001002028 Genome and transcriptome sequence data from a pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 3
EGAD00001002038 Genome and transcriptome sequence data from a peripheral T cell lymphoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 4
EGAD00001001310 Genome and transcriptome sequence data from a peritoneal mesothelioma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 2 bam
EGAD00001001311 Genome and transcriptome sequence data from a peritoneal mesothelioma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 3 bam
EGAD00001002043 Genome and transcriptome sequence data from a recurrent glioma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 2
EGAD00001002040 Genome and transcriptome sequence data from a squamous cell carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 3
EGAD00001002032 Genome and transcriptome sequence data from an adenoid cystic carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 3
EGAD00001002049 Genome and transcriptome sequence data from an adrenal cortical carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 2
EGAD00001002024 Genome and transcriptome sequence data from an anal rectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 3
EGAD00001001656 Genome and transcriptome sequence data from an atypical chronic lymphocytic leukemia patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 2 bam
EGAD00001001655 Genome and transcriptome sequence data from an atypical teratoid rhabdoid tumor patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 3 bam
EGAD00001002042 Genome and transcriptome sequence data from an endometrial cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 3
EGAD00001001658 Genome and transcriptome sequence data from an odontogenic ghost cell carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 2 bam
EGAD00001002039 Genome and transcriptome sequence data from an ovarian cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 3
EGAD00001002029 Genome and transcriptome sequence data from an ovarian granulosa patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 3
EGAD00001002037 Genome sequence data from an adrenal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 2
EGAD00001001389 Genome wide CRISPR screen was performed to find resistance to targeted drugs for melanoma and lung Illumina HiSeq 2500; 15 cram
EGAD00010000450 Genome Wide Genotype Data Illumina Human Custom 1,2M and Human 610 Quad Custom arrays 758
EGAD00001000677 Genome-wide analysis of H3K27me3 occupancy and DNA methylation in K27M-mutant and H3.3-WT primary pediatric high-grade gliomas (pHGGs) as well as pediatric pHGG cell lines. The study aims to elucidate the connection between K27M-induced H3K27me3 reduction and changes in DNA methylation as well as gene expression. Illumina HiSeq 2000; 19 fastq
EGAD00001001659 Genome-wide analysis of mutations induced by ionizing radiation in human cells in different conditions. HiSeq X Ten; 12 cram
EGAD00010000692 Genome-wide DNA methylation epigenotyping of African rainforest hunter-gatherers and neighbouring agriculturalists by Illumina HumanMethylation450 372
EGAD00010000496 Genome-wide SNP genotyping of African rainforest hunter-gatherers and neighbouring agriculturalists Illumina HumanOmni1-Quad-Illumina GenomeStudio 260
EGAD00010000690 Genome-wide SNP genotyping of African rainforest hunter-gatherers and neighbouring agriculturalists by Illumina HumanOmniExpress 160
EGAD00010000902 Genome-wide study of resistance to severe malaria in eleven worldwide populations:Gambia Illumina Omni 2.5M 5,594
EGAD00010000904 Genome-wide study of resistance to severe malaria in eleven worldwide populations:Kenya Illumina Omni 2.5M 3,865
EGAD00000000043 GenomeEUtwin control samples Illumina HumanHap300-Duo, Illumina HumanHap 550K 2,099
EGAD00000000040 GenomEUtwin Danish (DK) samples Illumina HumanHap 300 162
EGAD00000000042 GenomEUtwin Finnish (FIN) samples Illumina HumanHap 300 153
EGAD00000000041 GenomEUtwin Swedish (SWE) samples Illumina HumanHap 300 302
EGAD00001000272 Genomic Alterations in Gingivo-buccal Cancer: ICGC-India Project_YR01 454 GS FLX Titanium;, Illumina HiSeq 2000; 200 bam
EGAD00001001446 Genomic and transcriptomic characterization of drug-resistant colon cancer stem cell lines. Illumina HiSeq 2000; 4 cram
EGAD00001001265 Genomic architecture of mesothelioma parent study is project 925. This project is set up in parallel to project 925 in order to Whole genome sequence ten of the 59 tumours in that project. HiSeq X Ten; 18 cram
EGAD00001001039 Genomic characterisation of a large series of cancer cell lines. Illumina HiSeq 2000; 1,072 bam,cram
EGAD00001001852 Genomic DNA from Belgian control individuals was pooled. Then the genomic sequence of brain expressed miRNA genes was determined in the pools. Illumina MiSeq; 39 fastq
EGAD00001001850 Genomic DNA from Swedish control individuals was pooled. Then the genomic sequence of brain expressed miRNA genes was determined in the pools. Illumina MiSeq; 149 fastq
EGAD00001000947 Genomic libraries (500 bps) will be generated from total genomic DNA derived from Colorectal cancer patients and subjected to short paired end sequencing on the llumina platform. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions. Illumina HiSeq 2000; 45 cram
EGAD00001000367 Genomic libraries (500 bps) will be generated from total genomic DNA derived from lung cancer patients and subjected to short paired end sequencing on the llumina platform. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions. Illumina HiSeq 2000; 5 bam
EGAD00001000388 Genomic libraries (500 bps) will be generated from total genomic DNA derived from lung cancer patients and subjected to short paired end sequencing on the llumina platform. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions. Illumina HiSeq 2000; 15 bam
EGAD00001000368 Genomic libraries (500 bps) will be generated from total genomic DNA derived from Osteosarcoma cancer patients and subjected to short paired end sequencing on the llumina platform. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions. Illumina HiSeq 2000; 3 bam
EGAD00001000783 Genomic libraries will be generated from total genomic DNA derived from 200+ patients with childhood Transient Myeloproliferative Disorder (TMD) and or Acute Megakaryocytic Leukemia (AMKL) as well some matched constitutional samples (n < 50 ). Libraries will be enriched for a selected panel of genes using a bespoke pulldown protocol. 96 Samples will be individually barcoded and subjected to up to two lanes of Illumina HiSeq. Paired reads will be mapped to build 37 of the human reference genome to facilitate the characterisation of known gene mutations in cancer as well as the validation of potentially novel variants identified by prior exome sequencing. Illumina HiSeq 2000; 400 cram
EGAD00001000879 Genomic libraries will be generated from total genomic DNA derived from 200+ patients with childhood Transient Myeloproliferative Disorder (TMD) and or Acute Megakaryocytic Leukemia (AMKL) as well some matched constitutional samples (n < 50). Libraries will be enriched for a selected panel of genes using a bespoke pulldown protocol. 96 Samples will be individually barcoded and subjected to up to two lanes of Illumina HiSeq. Paired reads will be mapped to build 37 of the human reference genome to facilitate the characterisation of known gene mutations in cancer as well as the validation of potentially novel variants identified by prior exome sequencing. Illumina HiSeq 2500; 335 cram
EGAD00001000747 Genomic libraries will be generated from total genomic DNA derived from 4000 samples with Acute Myeloid Leukaemia. Libraries will be enriched for a selected panel of genes using a bespoke pulldown protocol. 64 Samples will be individually barcoded and subjected to up to one lanes of Illumina HiSeq. Paired reads will be mapped to build 37 of the human reference genome to facilitate the characterisation of known gene mutations in cancer as well as the validation of potentially novel variants identified by prior exome sequencing. Illumina HiSeq 2000; 2,734 cram
EGAD00000000045 Genomic sequencing and transcriptome shotgun sequencing of a metastatic tumour and its recurrence after drug therapy in a single patient Illumina Genome Analyzer II 1
EGAD00001000080 Genomics of Colorectal Cancer Metastases - Massively Parallel Sequencing of Matched Primary and Metastatic tumours to Identify a Metastatic Signature of Somatic Mutations (MOSAIC) Illumina HiSeq 2000, Illumina HiSeq 2000; 351 bam,cram
EGAD00001001661 Genotype and exome data for an Australian Aboriginal population: a reference panel for health-based research. 72 vcf
EGAD00010000872 Genotyped case and control sampes using HumanExome Beadchip 1,610
EGAD00010000652 Genotyped samples using Illumina HumanOmni2.5 402
EGAD00000000122 Genotypes at MITF E318K variant Illumina HumanHap 300 v2 Duo, Illumina HumanCNV370, Illumina Human660W-Quad 1,925
EGAD00000000121 Genotypes at MITF E318K variant Taqman and sequencing 2,488
EGAD00000000119 Genotypes from cell lines derived from breast carcinoma tissue Affymetrix 6.0 51
EGAD00010000650 Genotypes from Omni2.5 chip 1,213
EGAD00010000944 Genotyping data from Southeast Borneo individuals Illumina Human Omni Express Bead Chip-24 v1.0 41
EGAD00010000847 Genotyping using Affymetrix SNP6.0 49
EGAD00010000748 Genotyping using Illumina Human OmniExpress12v1.0 1
EGAD00010000752 German glioma case germline genotypes using Illumina HumanExome-12v1_A array Illumina HumanExome-12v1_A 899
EGAD00010000750 German glioma control germline genotypes using Illumina HumanExome-12v1_A array Illumina HumanExome-12v1_A 2,391
EGAD00001002211 Given the central importance of Africa to studies of human origins, genetic diversity and disease susceptibility, large-scale and representative characterisation of genetic diversity in Africa is needed. Analyses of ancient DNA from Africa would complement sequencing of modern African populations and provide unique opportunities to transform our understanding of the pre-history of the region. This approach would greatly refine our understanding of population structure and gene flow in Africa and globally, including genetic signatures of ancient admixture. This low coverage sequencing experiment will allow us to test and refine our pipeline for ancient DNA sequencing. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ Illumina HiSeq 2000; 6
EGAD00001000090 Glioma cell lines rearrangement screen Illumina Genome Analyzer II 3 bam
EGAD00010000688 glioma normal samples using 250K 119
EGAD00010000684 glioma normal samples using cytoscan 3
EGAD00010000682 glioma samples tumor using 250K 762
EGAD00010000686 glioma samples tumor using cytoscan 5
EGAD00001002206 Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from Africa have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene-disease association signals. A systematic assessment of genetic diversity within Africa would facilitate genomic epidemiological studies in the region. The GDA Project focus on sequencing the whole genome of less studied, genetically diverse groups within Africa with the objective of detailed characterisation of genetic variation within Africa. As part of this effort we propose to sequence at high depth (30x) on the Illumina X Ten platform nine individuals, including family trios wherever possible, from three distinct ethno-linguistic groups. This set of nine high depth genomes will serve as a high-confidence set to validate calling and filtering of variants in lower depth data. Additionally, it will complement existing data from the Human Genome Diversity Project (HGDP). A family-based design might also serve other projects (e.g. estimating TMRCA or mutation rate). HiSeq X Ten; 9
EGAD00001002209 Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from SSA have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene-disease association signals. A systematic assessment of genetic diversity within SSA would facilitate genomic epidemiological studies in the region. The African Genome Variation Project (AGVP) is an international collaboration that aims to produce a comprehensive catalogue of human genetic variation in SSA. This resource has extended our understanding of population history, patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies. The Genome Diversity in Africa Project (GDAP) will extend and expand the African Genome Variation (AGV) project. Using a sequencing-based approach, GDA project aims to produce a comprehensive catalogue of human genetic variation in SSA, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies in SSA populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out low and high depth whole genome sequencing of up to 2000 individuals across Africa (100 individuals from each ethnolinguistic group), and complement these data with 2.5M Illumina genotyping. We have already completed sequencing of 700 individuals across SSA, we are now adding an additional 540 samples from various ethno-linguistic groups within Africa, including populations from Burkina Faso, Morocco, Ghana, Nigeria, Kenya and South Africa. Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from SSA accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across SSA; 3) develop a cost-efficient, next-generation genotype array for diverse populations across SSA; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformatics. HiSeq X Ten; 25
EGAD00001002223 Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from SSA have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene-disease association signals. A systematic assessment of genetic diversity within SSA would facilitate genomic epidemiological studies in the region. The African Genome Variation Project (AGVP) is an international collaboration that aims to produce a comprehensive catalogue of human genetic variation in SSA. This resource has extended our understanding of population history, patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies. The Genome Diversity in Africa Project (GDAP) will extend and expand the African Genome Variation (AGV) project. Using a sequencing-based approach, GDA project aims to produce a comprehensive catalogue of human genetic variation in SSA, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies in SSA populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out low coverage (4x) whole genome sequencing of up to 2000 individuals across Africa (100 individuals from each ethnolinguistic group), and complement these data with 2.5M Illumina genotyping. We have already completed sequencing of 700 individuals across SSA, we are now adding an additional 500 samples from up to 5 ethno-linguistic groups within Africa, including populations from Burkina Faso, Cameroon, Morocco, Ghana and Seychelles. Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from SSA accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across SSA; 3) develop a cost-efficient, next-generation genotype array for diverse populations across SSA; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformatics. HiSeq X Ten; 25
EGAD00001002222 Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from SSA have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene-disease association signals. A systematic assessment of genetic diversity within SSA would facilitate genomic epidemiological studies in the region. The African Genome Variation Project (AGVP) is an international collaboration that aims to produce a comprehensive catalogue of human genetic variation in SSA. This resource has extended our understanding of population history, patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies. The Genome Diversity in Africa Project (GDAP) will extend and expand the African Genome Variation (AGV) project. Using a sequencing-based approach, GDA project aims to produce a comprehensive catalogue of human genetic variation in SSA, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies in SSA populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out low coverage (4x) whole genome sequencing of up to 2000 individuals across Africa (100 individuals from each ethnolinguistic group), and complement these data with 2.5M Illumina genotyping. We have already completed sequencing of 700 individuals across SSA, we are now adding an additional 500 samples from up to 5 ethno-linguistic groups within Africa, including populations from Burkina Faso, Cameroon, Morocco, Ghana and Seychelles. Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from SSA accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across SSA; 3) develop a cost-efficient, next-generation genotype array for diverse populations across SSA; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformatics. HiSeq X Ten; 25
EGAD00001000029 Grey Platelet Syndrome (GPS) Illumina Genome Analyzer II 5 srf
EGAD00001001268 H9 human embryonic stem cells (hESCs) were cultured in feeder-free chemically-defined conditions in medium containing 10ng/ml Activin A and 12ng/ml FGF2 (Vallier L. 2011, Methods in Molecular Biology, 690: 57-66). Chromatin immunoprecipitation was performed as described in Brown S. et al. 2011. Stem Cells 29: 1176-85 by using 5ug of anti-DPY30 antibody (Sigma, cat. number HPA043761). This protocol was performed in control hESCs (expressing a scrambled shRNA) and in hESCs stably expressing an shRNA against DPY30 (Sigma, clone n. TRCN0000131112). This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ Illumina HiSeq 2000; 4 cram
EGAD00010000419 Han Chinese samples using Affymetrix (cases) Affymetrix_6.0 62
EGAD00010000421 Han Chinese samples using Affymetrix (controls) Affymetrix_6.0 187
EGAD00010000417 Han Chinese samples using Illumina OMNIExpress (cases) Illumina OMNIExpress 62
EGAD00010000423 Han Chinese samples using Illumina OMNIExpress (controls) Illumina OMNIExpress 213
EGAD00010000425 Han Chinese samples using Immunochip HanChinese_Immunochip 192
EGAD00010000694 HCC array for cnv 55
EGAD00001001899 HDAC and PI3K Antagonists Cooperate to Inhibit Growth of MYC-driven Medulloblastoma 102 bam
EGAD00010000892 Healthy individuals from Italy Illumina 300
EGAD00001001081 Healthy reference samples 3 bam
EGAD00010000144 Healthy volunteer collection of European Ancestry Illumin OmniExpress v1.0 - Illumina GenomeStudio 288
EGAD00010000520 Healthy volunteer collection of European Ancestry Illumina OmniExpress v1.0-Illumina GenomeStudio 144
EGAD00001000204 Hearing loss in adults from South Carolina Illumina HiSeq 2000; 10 bam
EGAD00001000032 Hepatitis C IL28B pooled resequencing study with 100 responders and 100 non-responders Illumina Genome Analyzer IIx 4 Illumina_native
EGAD00001000126 HER2 positive Breast Cancer Illumina HiSeq 2000, Illumina HiSeq 2000; 101 bam,cram
EGAD00001000735 Here we present the genomes of three secondary angiosarcomas Illumina HiSeq 2000; 7 bam
EGAD00001001943 Here, we studied well-phenotyped individuals from the Flemish Gut Flora Project (FGFP, N=1,106, Belgium) and the effect of environments on microbiome. The 69 major significant phenotypes found in this study are provided. 1,106 phenotype_file
EGAD00001000807 High grade glioma whole exome sequencing Illumina HiSeq 2000; 148 bam
EGAD00001000806 High grade glioma whole genome sequencing (batch 2) Illumina HiSeq 2000; 63 bam
EGAD00001000277 High Quality Variant Call files, generated by bioscope, converted to vcf format. Complete dataset for all 300 samples. 300 vcf
EGAD00001000974 High-grade serous ovarian cancer (HGSC) is characterized by poor outcome, often attributed to emergence of treatment-resistant sub-clones. We sought to measure the degree of genomic diversity within primary, untreated HGSC to examine the natural state of tumor evolution prior to therapy. We performed exome sequencing, copy number analysis, targeted amplicon deep sequencing and gene expression profiling on thirty-one spatially and temporally separated HGSC tumor specimens (six patients) including ovarian masses, distant metastases, and fallopian tube lesions. We found widespread intra-tumoral variation in mutation, copy number, and gene expression profiles, with key driver alterations in genes present in only a subset of samples (e.g. PIK3CA, CTNNB1, NF1). On average, only 51.5% of mutations were present in every sample of a given case (range: 10.2% to 91.4%), with TP53 as the only somatic mutation consistently present in all samples. Complex segmental aneuploidies, such as whole genome doubling, were present in a subset of samples from the same individual, with divergent copy number changes segregating independently of point mutation acquisition. Reconstruction of evolutionary histories showed one patient with mixed HGSC and endometrioid histology with common etiologic origin in the fallopian tube and subsequent selection of different driver mutations in the histologically distinct samples. In this patient, we observed mixed cell populations in the early fallopian tube lesion, indicating diversity arises at early stages of tumorigenesis. Our results reveal that HGSC exhibit highly individual evolutionary trajectories and diverse genomic tapestries prior to therapy, exposing an essential biological characteristic to inform future design of personalized therapeutic solutions and investigation of drug resistance mechanisms. Illumina MiSeq;, Illumina HiSeq 2000; 131 bam
EGAD00001000669 High-grade serous ovarian cancer (HGSC) is characterized by poor outcome, often attributed to the emergence of treatment-resistant subclones. We sought to measure the degree of genomic diversity within primary, untreated HGSCs to examine the natural state of tumour evolution prior to therapy. We performed exome sequencing, copy number analysis, targeted amplicon deep sequencing and gene expression profiling on 31 spatially and temporally separated HGSC tumour specimens (six patients), including ovarian masses, distant metastases and fallopian tube lesions. We found widespread intratumoural variation in mutation, copy number and gene expression profiles, with key driver alterations in genes present in only a subset of samples (eg PIK3CA, CTNNB1, NF1). On average, only 51.5% of mutations were present in every sample of a given case (range 10.2 to 91.4%), with TP53 as the only somatic mutation consistently present in all samples. Complex segmental aneuploidies, such as whole-genome doubling, were present in a subset of samples from the same individual, with divergent copy number changes segregating independently of point mutation acquisition. Reconstruction of evolutionary histories showed one patient with mixed HGSC and endometrioid histology, with common aetiologic origin in the fallopian tube and subsequent selection of different driver mutations in the histologically distinct samples. In this patient, we observed mixed cell populations in the early fallopian tube lesion, indicating that diversity arises at early stages of tumourigenesis. Our results revealed that HGSCs exhibit highly individual evolutionary trajectories and diverse genomic tapestries prior to therapy, exposing an essential biological characteristic to inform future design of personalized therapeutic solutions and investigation of drug-resistance mechanisms Illumina Genome Analyzer; 25 bam
EGAD00001002010 high-throughput sequencing of methylated and hydroxymethylated DNA from tumor and non-tumor tissue of patients with high-risk prostate cancer Illumina HiSeq 2000; 32
EGAD00001000994 HIPO blastemal Wilms (nephroblastoma) characterisation of tumor driving chromosomal aberrations Illumina HiSeq 2000;, Illumina HiSeq 2500; 56 fastq
EGAD00001000995 HIPO blastemal Wilms (nephroblastoma) characterisation of tumor driving DNA alterations Illumina HiSeq 2000; 112 fastq
EGAD00001000992 HIPO blastemal Wilms (nephroblastoma) characterisation of tumor driving events caused by differential SIX1 binding of the SIX1 Q177R mutatns Illumina HiSeq 2500; 3 fastq
EGAD00001000993 HIPO blastemal Wilms (nephroblastoma) characterisation of tumor driving gene expression events Illumina HiSeq 2000; 40 fastq
EGAD00010000909 HipSci normal ES lines REL-2016-04 Illumina 2
EGAD00010000910 HipSci normal ES lines REL-2016-04 Illumina 2
EGAD00010000911 HipSci normal ES lines REL-2016-04 Illumina 2
EGAD00010000773 HipSci normal samples REL-2014-11 Illumina 580
EGAD00010000775 HipSci normal samples REL-2014-11 Illumina 580
EGAD00010000771 HipSci normal samples REL-2015-04 135
EGAD00010000568 HipSci normal samples using 450K 24
EGAD00010000564 HipSci normal samples using 47K 120
EGAD00010000566 HipSci normal samples using 500K 120
EGAD00001000897 HipSci-RNAseq_REL-2014-05_RNAseq_healthy volunteers Illumina HiSeq 2000; 22 cram
EGAD00001001438 HipSci-RNAseq_REL-2015-04_RNA sequencing_healthy volunteers Illumina HiSeq 2000; 131 cram
EGAD00001001933 HipSci-RNAseq_REL-2016-01_RNA sequencing_healthy volunteers Illumina HiSeq 2000; 181
EGAD00001000893 HipSci-WES_REL-2014-05_Whole exome sequencing_healthy volunteers Illumina HiSeq 2000; 15 cram
EGAD00001001437 HipSci-WES_REL-2015-04_Whole exome sequencing_healthy volunteers Illumina HiSeq 2000; 136 cram
EGAD00001001932 HipSci-WES_REL-2016-01_Whole exome sequencing_healthy volunteers Illumina HiSeq 2000; 262
EGAD00000000031 HLA genotyping of 1958 British Birth Cohort samples Dynal RELI SSO assay 6,662
EGAD00001000666 HSC73_clone: Bone marrow mononuclear cells from the healthy 73 years old female were thawed and labeled with Alexa-Fluor 488-conjugated anti-CD34 (581, Biolegend), Alexa-Fluor 700-conjugated anti-CD38 (HIT2, eBioscience), a cocktail of APC-conjugated lineage antibodies consisting of anti-CD4 (RPA-T4), anti-CD8 (RPA-T8), anti-CD11b (ICRF44), anti-CD20 (2H7), anti-CD56 (B159, all BD Biosciences), anti-CD14 (61D3), anti-CD19 (HIB19) and anti-CD235a (HIR2, all eBiocience) and 1 micro-gram/ml propidium iodide (Sigma). Using a BD FACSAria cell sorter, single Lin-CD34+CD38-PI- cells were individually sorted into low-adhesion 96-well tissue culture plates (Corning) containing 100micro-litre of StemSpan Serum-Free Expansion Medium (Stemcell technologies) supplemented with 100ng/ml of human SCF and FLT-3L, 50ng/ml of human TPO, 20ng/ml of human IL-3, IL-6 and G-CSF (all cytokines from Peprotech) and 50U/ml of penicillin and 50μg/ml of streptomycin (Sigma). Cells were incubated at 37 degrees C in a humidified atmosphere with 5% CO2 in air. After 5 days in culture, another 100micro litres of cytokine-containing medium were added. 13 days after seeding, clones B6 and G2 had expanded to approx. 105 cells and were selected for whole genome sequencing (2x101bp, paired-end, Illumina HiSeq2500) after tagmentation-based library preparation (see Extended Experimental Procedures) for clone B6 and standard library preparation for clone G2. For germline-control ~106 unsorted bone marrow mononuclear cells from the same donor were used for sequencing. An average of 30-fold sequence coverage for each the clones and the matching control were obtained. L4clone: A progenitor cell clone was raised from a peripheral blood sample of the 39 year old healthy female. Frozen peripheral blood mononuclear cells (PBMCs) were isolated from 2 ml heparinised peripheral blood via Ficoll Paque density centrifugation. A methylcellulose assay was performed as described earlier (Weisse et al., 2012). In brief, non-adherent mononuclear cells were incubated in the presence of the recombinant human cytokines IL-3, IL-5 and GM-CSF (R&D systems) over 14 days to induce colony formation. Colonies were detected under an inverted light microscope, and plucked by a pipette when colonies had approximately 10,000 cells/CFU. Each colony was washed three times in PBS and finally frozen as a cell pellet in -80 degrees C. Genomic DNA was isolated using the QIAamp DNA micro kit according to the instructions of the manufacturer (Qiagen, Hilden, Germany). Whole genome sequencing (2x101bp, paired-end, Illumina HiSeq2500) was performed for colony 4 after tagmentation-based library preparation and resulted in 15-fold sequence coverage for each the colony and the matching whole blood. 5 bam
EGAD00001000031 Human Colorectal Cancer Exome Sequencing Illumina Genome Analyzer II 16 srf
EGAD00001000362 Human induced pluripotent stem (hiPS) cells hold great promise for regenerative medicine. Safety issues of use of hiPS cells however remain to be addressed. One of such issues is mutations derived from somatic donor cells and introduced during genome manipulation. We sequence whole genomes of hiPS cells and analyzed mutations. Our study brings hiPS cell technology one step closer to application to regenerative medicine. Illumina HiSeq 2000; 7 bam
EGAD00001001306 Human melanoma samples were collected pre, on, and progression on BRAF inhibitor therapy. RNA was extracted and run on RNA-seq. This has provided insights into different categories of BRAF inhibitor resistance mechanisms. Illumina HiSeq 2000; 38 bam
EGAD00001001390 Human monocytes from a healthy male blood donor were obtained after written informed consent and anonymised. Library preparation was performed essentially as described in the “Whole‐genome Bisulfite Sequencing for Methylation Analysis (WGBS)” protocol as released by Illumina. The library was sequenced on an Illumina HiSeq2500 using 101 bp paired-end sequencing. Read mapping was done with BWA. 1 bam,readme_file
EGAD00010000708 Human samples typed on Illumina Omni 5M 124
EGAD00010000946 Human samples, 450k analysis Illumina 450k 127
EGAD00010000616 HumanOmni1-Quad genotyping array 230
EGAD00001000038 Hyperfibrinolysis Illumina Genome Analyzer II 5 bam
EGAD00001000260 Hypodiploid acute lymphoblastic leukemia whole genome sequencing Illumina HiSeq 2000; 40 bam
EGAD00001000027 ICGC Germany PedBrain Medulloblastoma Pilot_2_LM Illumina HiSeq 2000, Illumina Genome Analyzer IIx 8 bam
EGAD00001000816 ICGC medulloblastoma whole genome sequencing data, ICGC release 16 44 bam
EGAD00001000650 ICGC MMML-seq Data Freeze July 2013 miRNA sequencing 52 bam
EGAD00001000648 ICGC MMML-seq Data Freeze July 2013 transcriptome sequencing 31 bam
EGAD00001000645 ICGC MMML-seq Data Freeze July 2013 whole genome sequencing 42 bam
EGAD00001000356 ICGC MMML-seq Data Freeze March 2013 transcriptome sequencing Illumina HiSeq 2000; 23 bam
EGAD00001000355 ICGC MMML-seq Data Freeze March 2013 whole genome sequencing Illumina HiSeq 2000; 46 bam
EGAD00001000281 ICGC MMML-seq Data Freeze November 2012 transcriptome sequencing Illumina HiSeq 2000; 6 bam
EGAD00001000279 ICGC MMML-seq Data Freeze November 2012 whole exome sequencing Illumina Genome Analyzer IIx; 4 bam
EGAD00001000278 ICGC MMML-seq Data Freeze November 2012 whole genome sequencing Illumina HiSeq 2000; 12 bam
EGAD00001001595 ICGC PACA-CA Release 20 Illumina HiSeq 2000;, Illumina HiSeq 2500; 516 bam,fastq
EGAD00001002125 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: BOCA-UK. 148
EGAD00001002129 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: BRCA-EU. 158
EGAD00001002122 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: BRCA-UK. 90
EGAD00001002121 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: BTCA-SG. 24
EGAD00001002130 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: CLLE-ES. 194
EGAD00001002124 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: EOPC-DE. 113
EGAD00001002156 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: ESAD-UK. 198
EGAD00001002119 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: LAML-KR. 18
EGAD00001002016 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: LICA-FR. 12
EGAD00001002155 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: LIRI-JP. 524
EGAD00001002123 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: MALY-DE. 202
EGAD00001002157 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: MELA-AU. 140
EGAD00001002120 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: ORCA-IN. 26
EGAD00001002132 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PACA-AU. 192
EGAD00001002154 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PAEN-AU. 98
EGAD00001002153 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PAEN-IT. 74
EGAD00001002127 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PBCA-DE. 496
EGAD00001002128 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PRAD-CA. 244
EGAD00001002126 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PRAD-UK. 116
EGAD00001000644 ICGC PedBrain DNA Methylation project Illumina HiSeq 2000; 42 fastq
EGAD00001000328 ICGC PedBrain: RNA sequencing Illumina HiSeq 2000; 28 fastq
EGAD00001000304 ICGC prostate cancer miRNA sequencing Illumina HiSeq 2000; 8 fastq
EGAD00001000305 ICGC prostate cancer RNA sequencing Illumina HiSeq 2000; 12 fastq
EGAD00001000303 ICGC prostate cancer whole genome mate-pair sequencing Illumina Genome Analyzer IIx; 22 bam
EGAD00001000306 ICGC prostate cancer whole genome sequencing Illumina HiSeq 2000; 22 bam
EGAD00001001956 ICGC Release 21 for PACA-CA from OICR Illumina HiSeq 2000;, Illumina HiSeq 2500; 516
EGAD00001001428 Identification of human deubiquitylating enzymes whose knock out result in hypersensitivity to DNA damaging agents, by comparing the sequence reads of 'barcode region' from mixed cell culture. Illumina HiSeq 2000; 6 cram
EGAD00001000175 Identification of SPEN as a novel cancer gene and FGFR2 as a potential therapeutic target in adenoid cystic carcinoma Illumina Genome Analyzer II; 48 bam
EGAD00001000018 Identifying causative mutations for Thrombocytopenia with Absent Radii Illumina Genome Analyzer II 5 bam
EGAD00001000112 Identifying Novel Fusion Genes in Myeloma Illumina Genome Analyzer II 6 bam
EGAD00001000883 Illumina HiSeq paired-end exome sequencing of a trio and singleton. Illumina HiSeq 2000; 4 bam
EGAD00001000697 Illumina HiSeq sequence data (with >30x coverage) were aligned to the hg19 human reference genome assembly using BWA (Li and Durbin, 2009); duplicate reads were removed from the final BAM file. No realignment or recalibration was performed. Illumina HiSeq 2000;, Illumina Genome Analyzer IIx; 90 bam
EGAD00001000665 Illumina HiSeq sequence data (with >30x coverage) were aligned to the hg19 human reference genome assembly using BWA (Li and Durbin, 2009); duplicate reads were removed from the final BAM file. No realignment or recalibration was performed. Sample derived from secondary myelodysplastic syndrome (MDS), arising after treatment for medulloblastoma in an 11-year old female Li-Fraumeni syndrome case (LFS-MB1; Rausch et al., 2012; matching WGS data available under EGAS00001000085). 1 bam
EGAD00001000698 Illumina HiSeq sequence data (with >80x coverage) were aligned to the hg19 human reference genome assembly using BWA (Li and Durbin, 2009); duplicate reads were removed from the final BAM file. No realignment or recalibration was performed. The whole exome sequencing data of 20 SHH medulloblastomas from phs000504.v1.p1 dataset has been used in our study on SHH medulloblastomas: http://www.ncbi.nlm.nih.gov/projects/gap/cgi- bin/study.cgi?study_id=phs000504.v1.p1 4 bam
EGAD00001000699 Illumina HiSeq sequence data (with >80x coverage) were aligned to the hg19 human reference genome assembly using BWA (Li and Durbin, 2009); duplicate reads were removed from the final BAM file. No realignment or recalibration was performed. Illumina HiSeq 2000; 78 bam
EGAD00010000436 Illumina HT 12 IDAT files Illumina HT 12 1,302
EGAD00010000162 Illumina HT 12 IDATS Illumina HT 12 2,136
EGAD00010000160 Illumina HT 12 IDATS Illumina HT 12 1,001
EGAD00010000532 Illumina Human Omni1-Quad SNP genotyping array 0
EGAD00010000807 Illumina HumanCoreExome genotyping data from the British Society for Surgery of the Hand Genetics of Dupuytren's Disease consortium (BSSH-GODD consortium) collection 4,201
EGAD00010000528 Illumina HumanHT-12 v4 array 0
EGAD00010000534 Illumina HumanMethylation450 BeadChip 0
EGAD00010000791 Illumina HumanOmni2.5-8 BeadChip 1
EGAD00010000829 Illumina Infinium 450K array data 70
EGAD00010000827 Illumina Infinium 450K array data 1
EGAD00001000380 Illumina paired-end sequencing of whole- exome pulldown DNA from Severe Insulin Resistant patients. Illumina Genome Analyzer II;, Illumina HiSeq 2000; 64 bam
EGAD00001000381 Illumina paired-end sequencing of whole- exome pulldown DNA from Severe Insulin Resistant patients. Illumina HiSeq 2000; 3 bam
EGAD00001000337 Illumina RNA-Seq will be performed on four Ewing's sarcoma cell lines and two control cell lines. RNA was extracted from all the lines using a basic Trizol extraction protocol. Illumina HiSeq 2000; 12 bam
EGAD00010000908 Illumina SNP-arrays for matching retinoblastoma-blood pairs and retinoblastoma cell lines. HumanOmni1 Quad BeadChip 132
EGAD00001001983 Immunoglobulin heavy chain gene high throughput sequencing of paediatric acute lymphoblastic leukaemia samples, for the purpose of MRD on the Illumina MiSeq platform. This dataset contains summary fastq files and raw bcl files from the MiSeq for this study. In the study we identify errors associated with multiplexing that could potentially impact on the accuracy of MRD analysis. We optimise a strategy combining high purity, sequence-optimised oligonucleotides, dual-indexing and an error-aware demultiplexing approach to minimise errors and maximise sensitivity. Illumina MiSeq; 491 fastq
EGAD00001000399 In 2009 we identified a four-generation family with over 700 members and 41 affected with Crohn's disease (CD). At the time we sequenced the exome of 6 affected individuals but did not identify any coding variants which appear to explain the high prevalence of disease. Since then we have collected DNA from a large number of additional family members, genotyped linkage arrays on the entire family to refine genomic regions shared by identity by descent and genotyped affected and unaffected members at known CD risk loci identified by Genome Wide Association Studies (GWAS). These analyses have confirmed that a significant unexplained excess of disease remains after accounting for all known genetic factors, and that several regions of the genome are shared by a large fraction of affected individuals. We therefore perform whole genomes sequencing from 8 individuals which will allow us to impute the complete sequence of nearly all the members of the two largest and most severely affected branches of the family. Illumina HiSeq 2000; 8 bam
EGAD00001002227 In collaboration with Dr David Savage, we have identified a patient with a very unusual phenotype, lacking almost all visceral fat, but showing a massive accumulation of white fat tissue behind her neck and significantly elevated liver fat. Whole exome sequencing of the proband and her unaffected parents and brother has been run previously, however no causative variant has been found and the sequencing coverage was generally poor. We propose to conduct whole genome sequencing of all 4 family members at a depth of 30X. HiSeq X Ten; 3
EGAD00001000383 In collaboration with Dr Robert Semple we have identified a family harbouring an autosomal dominant variant, which leads to severe insulin resistance (SIR), short stature and facial dysmorphism. This family is unique within the SIR cohort in having normal lipid profiles, preserved adiponectin and normal INSR expression and phosphorylation. DNA is available for 7 affected and 7 unaffected family members across 3 generations. All 14 samples have been genotyped using microsatellites and the Affymetrix 6.0 SNP chip. Linkage analysis identified an 18.8Mb haplotype on chromosome 19 as a possible location of the causative variant. However, Exome sequencing of 3 affected and 1 unaffected family members has not identified the causative variant suggesting the possibility of an intronic or intergenic variant in this region or elsewhere in the genome. We propose to conduct whole genome sequencing of 5 members of the pedigree at a depth of 20X. The chosen samples are two sets of parents plus one member of an unaffected branch of the pedigree who shares the risk haplotype on chromosome 19. Sequencing of the two sets of parents will be used along with the genome-wide SNP data to impute 4 affected children giving an effect sample size of 6 affected individuals. Illumina HiSeq 2000; 7 bam
EGAD00001000884 In order to elucidate whether newly acquired genetic alterations during serial transplantation of patient derived primary pancreatic cancer cultures contribute to the observed clonal dynamics in vivo, all coding genes of two patient derived primary cultures and derived genetically marked serial xenografts (1°/2°/3°) were sequenced. Illumina HiSeq 2000; 10 fastq
EGAD00001000761 In order to establish copy number profiles from the various samples we prepared libraries and subjected them to whole-genome sequencing at a shallow sequencing depth (0.1x) Illumina MiSeq; 14 fastq
EGAD00001000798 In order to progress human induced pluripotent stem cells (hiPSCs) towards the clinic, several outstanding questions must be addressed. It is possible to reprogram different somatic cell types into hiPSCs but it is unclear whether some cell types carry through fewer mutations through reprogramming (either due to mutations present in the primary cells, or mutations accumulated during reprogramming). Through in depth analysis of hiPSCs generated from different somatic cells, it will be possible to assess the variation in genetic stability of different cell types. Illumina MiSeq;, Illumina HiSeq 2000; 28 bam
EGAD00001000384 In order to progress human induced pluripotent stem cells (hiPSCs) towards the clinic, several outstanding questions must be addressed. It is possible to reprogram different somatic cell types into hiPSCs but it is unlcear whether some cell types carry through fewer mutations through reprogramming (either due to mutations present in the primary cells, or mutations accumulated during reprogramming). Through in depth analysis of hiPSCs generated from different somatic cells, it will be possible to assess the variation in genetic stability of different cell types. Illumina HiSeq 2000; 35 bam
EGAD00001001686 In the autozygosity exome sequencing of Born-in-Bradford samples of Pakistani origin there is a mother who is homozygous for an apparent truncating stop codon in PRDM9, the gene responsible for localising recombination during meiosis. We plan to deep sequence mother and child with X10, and physically phase the mother with PacBio sequencing. We will use this data to identify recombination locations, and test whether these are consistent with the known fine scale recombination map. Illumina HiSeq 2500; 2 cram
EGAD00001001853 In this dataset are the data from : - 17 patients studied by WGS - 49 patients studied by WES - 9 (/49) patients studied by RNASeq at 2 time points - the same 9 patients studied by ERRBS at 2 time points Illumina HiSeq 2000; 199 fastq
EGAD00001001607 In this dataset, 16 trios- primary tumor, relapse and corresponding normals- for patients with neuroblastoma are provided. For one patient, more than one relapse was available for the analyses. Illumina HiSeq 2000; 50 bam
EGAD00001001330 In this experiment we have sequenced tumour normal pairs from patients presenting with CRC who have a prior history of inflammatory bowel disease. The idea is to identify driver mutations, new genes and novel pathways associated with the development of these malignancies. Illumina HiSeq 2000; 70 cram
EGAD00001000405 In this project we will sequence the exomes of 250 patients with Parkinson's disease Illumina HiSeq 2000; 247 bam
EGAD00001002050 In this project we will use exome sequencing to identify somatic mutations in lesions from a patient with a germline mutation in the protection of telomeres 1 gene (POT1). Illumina HiSeq 2000; 36
EGAD00001000365 In this study we analysed patients with metastatic prostate cancer to scan their tumor genomes noninvasively in plasma DNA. We enriched 1.3 Mbp of seven plasma DNAs (4 CRPC cases: CRPC1-3 and CRPC5; 3 CSPC cases: CSPC1-2 and CSPC4) including exonic sequences of 55 cancer genes and 38 introns of 18 genes, where fusion breakpoints have been described using Sure Select Custom DNA Kit. Illumina MiSeq; 7 fastq
EGAD00001000688 In this study we performed ultra deep sequencing of genes associated with anti-EGFR resistance, such as KRAS, BRAF, PIK3CA, and EGFR in 17 plasma-DNA samples from a total of 10 patients treated with anti-EGFR therapy. Illumina MiSeq; 25 bam
EGAD00001000748 In this study we performed whole genome sequencing of plasma DNA (plasma-Seq) of 19 plasma-DNA samples from a total of 10 patients treated with anti-EGFR therapy. We demonstrated that development of resistance to anti-EGFR therapies is frequently associated with focal amplifications of KRAS, MET, and ERBB2. We also showed that focal KRAS amplifications can be acquired in tumor genomes of patients under cytotoxic chemotherapy. Furthermore, we provide evidence that specific chromosomal polysomies, such as overrepresentations of 12p and 7p, harboring KRAS and EGFR, respectively, determine responsiveness to anti-EGFR therapy. Illumina MiSeq; 19 fastq
EGAD00001000359 In this study we will sequence the transcriptome of Verified Cancer Cell lines. This will be married up to whole exome and whole genome sequencing data to establish a full catalog of the variations and mutations found. Illumina HiSeq 2000; 2 bam
EGAD00001000630 In this study we will sequence the transcriptome of Verified Matched Pair Cancer Cell line tumour samples. This will be married up to whole exome and whole genome sequencing data to establish a full catalog of the variations and mutations found. Illumina HiSeq 2000; 7 bam
EGAD00001000325 In this study, mutations present in a series of human melanomas (stage IV disease) will be determined, using autologous blood cells to obtain a reference genome. From each of the samples that are analyzed, tumour-infiltrating T lymphocytes have also been isolated. This offers a unique opportunity to determine which (fraction of) mutations in human cancer leads to epitopes that are recognized by T cells. The resulting information is likely to be of value to understand how T cell activating drugs exert their action. Illumina HiSeq 2000; 22 bam
EGAD00001000726 In total 30 Acute Myeloid Leukemias with an acquired inv(3)(q21q26) or t(3;3)(q21;q26) have been characterized by whole transcriptome sequencing (RNA-Seq). The 3q-aberration leads to overexpression of the proto-oncogene EVI1, but the mechanism of overexpression has thus far been elusive. The RNA-Seq was integral in determining the precise enhancer inducing the overexpression and led to other key discoveries. Illumina HiSeq 2500; 30 fastq
EGAD00001000874 Indel/point mutation of chondrosarcoma 10 vcf
EGAD00010000897 Infinium 450K in Rhabdomyosarcoma Infinium HumanMethylation450 BeadChip 53
EGAD00001000638 Insertion of processed pseudogenes is known to occur in the germline but has not previously been observed in somatic cells. Formation of pseudogenes could represent a new class of mutation in cancers and a new source of potential driver events. Illumina HiSeq 2000; 20 bam
EGAD00001000637 Insertion of processed pseudogenes is known to occur in the germline but has not previously been observed in somatic cells. Formation of pseudogenes could represent a new class of mutation in cancers and a new source of potential driver events. Illumina Genome Analyzer II;, Illumina HiSeq 2000; 4 bam
EGAD00001000639 Insertion of processed pseudogenes is known to occur in the germline but has not previously been observed in somatic cells. Formation of pseudogenes could represent a new class of mutation in cancers and a new source of potential driver events. Illumina HiSeq 2000; 3 bam
EGAD00001000074 Integrative Oncogenomics of Multiple Myeloma Illumina HiSeq 2000, Illumina Genome Analyzer II 174 bam,srf
EGAD00001000246 Integrative Oncogenomics of multiple myeloma Illumina HiSeq 2000; 106 bam
EGAD00001000247 Integrative Oncogenomics of multiple myeloma Illumina HiSeq 2000; 51 bam
EGAD00001000288 Invasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer accounting for 10-15% of cases. ILC differs from invasive ductal carcinoma (IDC)with respect to epidemiology, histology, and clinical presentation. Moreover, ILC is less sensitive to chemotherapy, more frequently bilateral, and more prone to form gastrointestinal, peritoneal, and ovarian metastases than IDCs. In contrast to IDC, the prognostic value of histological grade (HG) in ILC is controversial. One of the three major components of histological grading (tubule formation) is missing in ILC which hinders the process of grading in this histological subtype and results in the classification of approximately two thirds of ILC as HG 2. Over the last decade, a number of gene expression signatures have shed light onto breast cancer classification, allowing breast cancer care to become more personalized. With respect to the management of estrogen receptor (ER)-positive breast cancer, several gene expression signatures provide prognostic and/or predictive information beyond what is possible with current classical clinico-pathological parameters alone. Nevertheless, most studies using gene expression signature have not considered different histologic subtypes separately. Recently, a comprehensive research program has elucidated some of the biological underpinnings of invasive lobular carcinoma. Genetic material extracted from 200 ILC tumor samples were studied using gene expression profiling and identified ILC molecular subtypes. These proliferation-driven gene signatures of ILC appear to have prognostic significance. In particular, the Genomic Grade (GG) gene signature improved upon HG in ILC and added prognostic value to classic clinico-pathologic factors. In addition this study demonstrated that most ILC are molecularly characterized as luminal-A (~75%)followed by luminal-B (~20%) and HER2-positve tumors (~5%). Moreover, we investigated the prognostic value of known gene signatures/ gene modules in the same cohort of ILC. As a second step within the scope of this project, we aim to investigate the interactions between somatic ILC tumor mutations to observed transcriptome findings. To this end, we aim to perform somatic mutation analysis for the ILC tumors for which Affymetrix gene expression profiling is available. To this end, we will use a gene screen assay, which specifically interrogates the mutational status of a few hundreds of cancer genes. We believe that this pioneering effort will be fundamental for a tailored treatment of ILC with improvement in patients' outcome. Illumina HiSeq 2000; 1,130 bam,cram
EGAD00001001430 Investigation into causal genes underlying anaplastic meningioma Illumina HiSeq 2000; 73 cram
EGAD00001000026 Investigation of the genetic basis of the rare syndrome Post-Transfusion Purpura (PTP) Illumina Genome Analyzer II 5 bam,srf
EGAD00010000618 Ischemic stroke cases 3,682
EGAD00001002014 Isolated populations have unique population genetics characteristics that can help boost power in genetic association studies for complex traits. Leveraging these advantageous characteristics requires an in-depth understanding of parameters that have shaped sequence variation in isolates. This study performs a comprehensive investigation of these parameters using low-depth whole genome sequencing (WGS) across multiple isolates. 6,840
EGAD00001000869 It is the ambition of the team formed by members of the Netherlands Cancer Institute (NKI) and the Cancer Genome Project at the Wellcome Trust Sanger Institute (WTSI) to unravel the genomic and phenotypic complexity of human cancers in order to identify optimal drug combinations for personalized cancer therapy. Our integrated approach will entail (i) deep sequencing of human tumours and cognate mouse tumours; (ii) drug screens in a 1000+ fully characterized tumour cell line panel; (iii) high-throughput in vitro and in vivo shRNA and cDNA drug resistance and enhancement screens; (iv) computational analysis of the acquired data, leading to significant response predictions; (v) rigorous validation of these predictions in genetically engineered mouse models and patient-derived xenografts. This integrated effort is expected to yield a number of combination therapies and companion-diagnostics biomarkers that will be further explored in our existing clinical trial networks. Illumina HiSeq 2000; 62 cram
EGAD00001001885 January 2016 update of RNA-Seq data (bams, fastqs) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium. Illumina HiSeq 2500; 17 fastq
EGAD00001001451 JMML targeted sequencing of candidate genes Illumina MiSeq; 75 bam
EGAD00001002239 June 2016 data update (bam/fastq for CEMT0062, CEMT0068, CEMT0072, CEMT0086, CEMT0087 ChIP-Seq and RNA-Seq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium. Illumina HiSeq 2500; 10
EGAD00001000071 Kaposi sarcoma exome Illumina HiSeq 2000 20 bam
EGAD00001002167 KNIH001 Data set, Whole-Genome Bisulfite Sequencing(WGBS) paired end data, mRNA-Seq paired end data and miRNA-Seq single end data for islet cells, Illumina HiSeq 2000;, Illumina HiSeq 2500; 3
EGAD00001002168 KNIH002 data set, Whole-Genome Bisulfite Sequencing(WGBS) paired end data, mRNA-Seq paired end data and miRNA-Seq single end data for islet cells Illumina HiSeq 2000;, Illumina HiSeq 2500; 3
EGAD00001002169 KNIH003 data set, Whole-Genome Bisulfite Sequencing(WGBS) paired end data, mRNA-Seq paired end data and miRNA-Seq single end data for islet cells Illumina HiSeq 2000;, Illumina HiSeq 2500; 3
EGAD00001002066 KRAS mutant CRC is currently in clinical trial with a combination of a MEK and Akt inhibitor. These patients will likely develop resistance to this combination. We aim to identify the mechanisms of resistance via ENU mutagenesis, with a view to identifying additional therapeutics which have the ability to overcome this resistance. Illumina HiSeq 2500; 86
EGAD00001001845 Leeds Melanoma Cohort Illumina HiSeq 2000; 16 cram
EGAD00001000019 Lethal malformation syndrome Illumina Genome Analyzer II 6 srf
EGAD00010000456 Leukemia samples using 450K DNA methylation 800
EGAD00001001666 LGG Epilepsy Cohort RNA-Seq Illumina HiSeq 2000; 34 bam
EGAD00001001664 LGG Epilepsy Cohort WGS Illumina HiSeq 2000; 18 bam
EGAD00001001665 LGG Epilepsy Cohort WXS Illumina HiSeq 2000; 61 bam
EGAD00001001250 Low coverage (4-6x) sequencing on samples from population cohorts (Finrisk, Health2000) will be done at Wellcome Trust Sanger Institute (WTSI) using Illumina HiSeq sequencing technology. We will produce 100bp paired end reads. Variants will be called using the 1000 Genomes Project pipeline. The samples have been selected from a national representative set of 8028 samples from persons of 30 years or older, which were screened for psychotic and bipolar disorders using the Composite International Diagnostic Interview, self-reported diagnoses, medical examination, and national registers. Illumina HiSeq 2000; 731 bam
EGAD00001001251 Low coverage (4-6x) sequencing on samples from population cohorts (Finrisk, Health2000) will be done at Wellcome Trust Sanger Institute (WTSI) using Illumina HiSeq sequencing technology. We will produce 100bp paired end reads. Variants will be called using the 1000 Genomes Project pipeline. The samples have been selected from a national representative set of approximately 30,300 samples and comprises 500 individuals of each gender in the extreme tail of high density lipoprotein (HDL) concentrations. Included individuals were between 25 and 65 years of age. Individuals with a diagnosis of diabetes or BMI>30 were excluded from the study. Illumina HiSeq 2000; 966 bam
EGAD00001001663 Low coverage (4x-8x) Illumina HiSeq curated sequence data from 3 African populations from the AGV project; 100 Baganda from Uganda (4x), 100 Zulu from South Africa (4x), and 120 Gumuz, Wolayta, Oromo, Somali and Amhara from Ethiopia (8x). Pre-processed, jointly called and filtered with GATK, refined with Beagle3, phased with SHAPEIT2. 1 vcf
EGAD00001002149 Low coverage whole genome sequencing for the identification of somatic copy number alterations (SCNA) and focal amplification mapping in plasma DNA of prostate cancer patients Illumina MiSeq; 95
EGAD00001002150 Low coverage whole genome sequencing for the identification of somatic copy number alterations (SCNA) and focal amplification mapping of corresponding tumor material Illumina MiSeq; 8
EGAD00001000728 Low coverage whole genome sequencing of samples from individuals from Friuli Venezia Giulia, an Italian genetic isolate population. Illumina HiSeq 2000; 199 bam
EGAD00001002215 Low coverage whole genome sequencing plasma DNA from 50 male, 54 female non-cancer donors. For the analysis of nucleosomal positioning all data from the non-cancer controls were merged. Furthermore, two patients with metastasized breast cancer were sequenced on a NextSeq with higher depth. NextSeq 550;, Illumina MiSeq; 108
EGAD00001001008 Low depth (4x) Illumina HiSeq raw sequence data for 100 unrelated Baganda from rural Uganda. Illumina HiSeq 2000; 100 bam
EGAD00001001007 Low depth (4x) Illumina HiSeq raw sequence data for 100 unrelated Zulu from Durban area, South Africa. Illumina HiSeq 2000; 100 bam,cram
EGAD00001001639 Low depth (4x) Illumina HiSeq raw sequence data for 2000 Ugandans from various ethno-linguistic group from rural South-West Uganda (related individuals included). Illumina HiSeq 2000; 2,000
EGAD00001000964 Low-coverage whole genome sequencing of sporadic schwannomatosis patients 16 bam
EGAD00001000144 Lung Cancer Whole Genomes Illumina HiSeq 2000, Illumina HiSeq 2000; 18 bam
EGAD00001000069 Lung Rearrangement Study Illumina HiSeq 2000 48 bam
EGAD00010000448 Macrophage Gene Expression Illumina Human-Ref-8 v3 beadchip 758
EGAD00001001439 Mammary cell samples from donors 28/32/33. Contains 12 MiSeq sequence files and 12 alignment files derived from HiSeq runs. Illumina MiSeq; 12 fastq
EGAD00001002231 Many studies over the past 10 years, culminating in the recent report of the International Stem Cell Initiative (ISCI, 2011) have shown that hPSC acquire genetic and epigenetic changes during their time in culture. Many of the genetic changes are non-random and recurrent, probably because they provide a selective growth advantage to the undifferentiated cells. Some are shared by embryonal carcinoma cells, the malignant counterparts of ES cells. The origins of these growth advantages are poorly understood, but may come from altered cell cycle dynamics, resistance to apoptosis or altered patterns of differentiation. Less is known about the nature and consequences of epigenetic changes, but it is likely that these similarly affect hPSC behaviour; e.g., enhanced expression of DLK1, an imprinted gene, is associated with altered hPSC growth (Enver et al 2005). Inevitably, these genetic and epigenetic changes will impact on our ability to use hPSC for regenerative medicine, either because malignant transformation of the undifferentiated cells or their differentiated derivatives to be used for transplantation compromises safety, or because they impede the function of those differentiated derivatives, or because they affect the efficiency with which the undifferentiated cells can be expanded and differentiated into desired cell types. Focusing initially upon the existing clinical grade hESC lines, later moving to iPSC, we will Consolidate and extend knowledge of the rate, type and functional impact of the genetic variations that occur during hPSC culture. We will use whole genome and exome sequencing as well as SNP arrays, together with clonal analysis and other cytogenetics techniques. Common changes will be compared with those found in the normal human population, at low frequency in the original cell population or observed during iPSC generation in the HIPSCI project currently based at the WTSI. These studies will provide a better understanding of the range of genetic changes that occur in hPSC beyond the CNVs already identified. In conjunction with cancer genome resources and expertise at WTSI, bioinformatic analyses of these hPSC data will allow us to assess potential impact on hPSC behaviour pertinent to applications in regenerative medicine, notably the likelihood that specific changes arising in undifferentiated PSC cultures may be associated with potential malignant transformation of differentiated progeny. This data is part of a pre-publication release. For information on the proper use of pre-publication data shred by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ HiSeq X Ten; 80
EGAD00001002235 Many studies over the past 10 years, culminating in the recent report of the International Stem Cell Initiative (ISCI, 2011) have shown that hPSC acquire genetic and epigenetic changes during their time in culture. Many of the genetic changes are non-random and recurrent, probably because they provide a selective growth advantage to the undifferentiated cells. Some are shared by embryonal carcinoma cells, the malignant counterparts of ES cells. The origins of these growth advantages are poorly understood, but may come from altered cell cycle dynamics, resistance to apoptosis or altered patterns of differentiation. Less is known about the nature and consequences of epigenetic changes, but it is likely that these similarly affect hPSC behaviour; e.g., enhanced expression of DLK1, an imprinted gene, is associated with altered hPSC growth (Enver et al 2005). Inevitably, these genetic and epigenetic changes will impact on our ability to use hPSC for regenerative medicine, either because malignant transformation of the undifferentiated cells or their differentiated derivatives to be used for transplantation compromises safety, or because they impede the function of those differentiated derivatives, or because they affect the efficiency with which the undifferentiated cells can be expanded and differentiated into desired cell types. Focusing initially upon the existing clinical grade hESC lines, later moving to iPSC, we will Consolidate and extend knowledge of the rate, type and functional impact of the genetic variations that occur during hPSC culture. We will use whole genome and exome sequencing as well as SNP arrays, together with clonal analysis and other cytogenetics techniques. Common changes will be compared with those found in the normal human population, at low frequency in the original cell population or observed during iPSC generation in the HIPSCI project currently based at the WTSI. These studies will provide a better understanding of the range of genetic changes that occur in hPSC beyond the CNVs already identified. In conjunction with cancer genome resources and expertise at WTSI, bioinformatic analyses of these hPSC data will allow us to assess potential impact on hPSC behaviour pertinent to applications in regenerative medicine, notably the likelihood that specific changes arising in undifferentiated PSC cultures may be associated with potential malignant transformation of differentiated progeny. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ Illumina HiSeq 2000; 80
EGAD00001002001 Mapped data (bam files) for high-throughput whole genome sequence data for 83 modern Aboriginal Australians 83 bai,bam
EGAD00001001939 Mapped whole transcriptome RNA-Seq data from 476 human samples of early stage urothelial carcinoma. Illumina HiSeq 2000; 476
EGAD00001002232 Mapping genetic evolution of pancreatic cancer precursor lesions such as IPMNs and PanINs. Illumina HiSeq 2000; 20
EGAD00001001959 March 2016 update of smRNA-Seq assays data (bam/fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium. Illumina HiSeq 2500; 20 fastq
EGAD00001001987 March 2016 update of Whole genome bisulfite sequencing assay data (bams) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium. 18 bam
EGAD00001001957 March 2016 update of Whole genome bisulfite sequencing assay data (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium. Illumina HiSeq 2500; 18 fastq
EGAD00001001958 March 2016 update of whole genome shotgun sequencing data (bam/fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium. Illumina HiSeq 2500; 17 fastq
EGAD00001000002 Massive genomic rearrangement acquired in a single catastrophic event during cancer development 11
EGAD00001000097 Matched breast cancer fusion gene study Illumina Genome Analyzer II 46 bam,srf
EGAD00010000510 Matched control samples using HumanOmni1-Quad GenomeWideSNP_6-BirdseedV2 12
EGAD00010000508 Matched control samples using SNP 6.0 Array GenomeWideSNP_6-BirdseedV2 12
EGAD00001000084 Matched Ovarian Cancer Sequencing Illumina Genome Analyzer II 23 bam
EGAD00001000145 Matched Pair Cancer Cell line Whole Genomes Illumina HiSeq 2000, Illumina HiSeq 2000; 58 bam
EGAD00010000050 Matched tumor-negative pancreas tissues Affymetrix SNP 6.0 15
EGAD00001002113 Mate pair whole genome sequencing data from 15 pediatric BCP ALL cases. Reference genome: hg19. Alignment: BWA 0.7.9a. NextSeq 500; 15
EGAD00001001609 Maternal Plasma RNA Sequencing for Genomewide Transcriptomic Profiling and Identification of Pregnancy-Associated Transcripts 14 bam
EGAD00001001300 McGill EMC Release 4 for assay "ATAC-seq": Sequencing of transposase-accessible chromatin as described by Buenrostro et al. (Nature Methods 10, 1213?1218 (2013) doi:10.1038/nmeth.2688) Illumina HiSeq 2500; 1 fastq
EGAD00001001289 McGill EMC Release 4 for assay "Bisulfite-seq": Methylation profiling by high-throughput sequencing Illumina HiSeq 2500; 44 fastq
EGAD00001001293 McGill EMC Release 4 for assay "ChIP-Seq Input" Illumina HiSeq 2500; 52 fastq
EGAD00001001298 McGill EMC Release 4 for assay "H3K27ac" Illumina HiSeq 2500; 36 fastq
EGAD00001001294 McGill EMC Release 4 for assay "H3K27me3" Illumina HiSeq 2500; 32 fastq
EGAD00001001295 McGill EMC Release 4 for assay "H3K36me3" Illumina HiSeq 2500; 37 fastq
EGAD00001001296 McGill EMC Release 4 for assay "H3K4me1" Illumina HiSeq 2500; 41 fastq
EGAD00001001297 McGill EMC Release 4 for assay "H3K4me3" Illumina HiSeq 2500; 42 fastq
EGAD00001001299 McGill EMC Release 4 for assay "H3K9me3" Illumina HiSeq 2500; 29 fastq
EGAD00001001291 McGill EMC Release 4 for assay "mRNA-seq": Transcriptome profiling by high-throughput sequencing Illumina HiSeq 2500; 40 fastq
EGAD00001001290 McGill EMC Release 4 for assay "RNA-seq": Transcriptome profiling by high-throughput sequencing Illumina HiSeq 2500; 261 fastq
EGAD00001001292 McGill EMC Release 4 for assay "smRNA-seq": Transcriptome profiling by high-throughput sequencing Illumina HiSeq 2500; 6 fastq
EGAD00001001276 McGill EMC Release 4 for cell type "induced pluripotent stem cell" Illumina HiSeq 2500; 8 fastq
EGAD00001001284 McGill EMC Release 4 in tissue "Brodmann (1909) area 11" Illumina HiSeq 2500; 1 fastq
EGAD00001001285 McGill EMC Release 4 in tissue "Brodmann (1909) area 44" Illumina HiSeq 2500; 1 fastq
EGAD00001001286 McGill EMC Release 4 in tissue "Brodmann (1909) area 8;Brodmann (1909) area 9" Illumina HiSeq 2500; 1 fastq
EGAD00001001277 McGill EMC Release 4 in tissue "fat pad" for cell type "fat cell" Illumina HiSeq 2500; 1 fastq
EGAD00001001287 McGill EMC Release 4 in tissue "kidney" Illumina HiSeq 2500; 2 fastq
EGAD00001001288 McGill EMC Release 4 in tissue "skeletal muscle tissue" Illumina HiSeq 2500; 29 fastq
EGAD00001001278 McGill EMC Release 4 in tissue "venous blood" for cell type "B cell" Illumina HiSeq 2500; 41 fastq
EGAD00001001279 McGill EMC Release 4 in tissue "venous blood" for cell type "CD4-positive helper T cell" Illumina HiSeq 2500; 55 fastq
EGAD00001001280 McGill EMC Release 4 in tissue "venous blood" for cell type "CD4-positive, alpha-beta T cell" Illumina HiSeq 2500; 40 fastq
EGAD00001001281 McGill EMC Release 4 in tissue "venous blood" for cell type "eosinophil" Illumina HiSeq 2500; 3 fastq
EGAD00001001282 McGill EMC Release 4 in tissue "venous blood" for cell type "Monocyte" Illumina HiSeq 2500; 82 fastq
EGAD00001001283 McGill EMC Release 4 in tissue "venous blood" for cell type "T cell" Illumina HiSeq 2500; 20 fastq
EGAD00001000201 MDACC-endo AB SOLiD System 3.0; 28 bam
EGAD00001001080 MDS patients 5 bam
EGAD00001000073 MDSMPN Rearrangement Screen Illumina HiSeq 2000, Illumina HiSeq 2000; 11 bam
EGAD00010000562 Medulloblastoma DNA methylation Illumina_HumanMethylation450 115
EGAD00001000243 Melanoma-TIL Study Exomes