What are Datasets?

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

Total number of Datasets: 2084
Displaying 1 - 2084

Dataset Accession Description Technologysort descending Samples File Types
EGAD00000000019 840 families where both parents have been genotyped together with the child with severe malaria 0
EGAD00001000002 Massive genomic rearrangement acquired in a single catastrophic event during cancer development 11
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
EGAD00001001856 100 other
EGAD00010000853 VeraCode GoldenGate GT Assay technology 147
EGAD00010000823 Results of SNP arrays on synchronous CRC samples 1
EGAD00001000277 High Quality Variant Call files, generated by bioscope, converted to vcf format. Complete dataset for all 300 samples. 300 vcf
EGAD00001000001 Exome sequencing identifies frequent mutation of the SWI/SNF complex gene PBRM1 in renal carcinoma 18
EGAD00000000020 685 families where both parents have been genotyped together with the child with severe malaria 0
EGAD00010000458 Controls using 450K DNA methylation 151
EGAD00010000742 Subset 1 of osteoarthritis cases genotyped on Illumina610k from the arcOGEN Consortium (http://www.arcogen.org.uk/) with broader consent. 5,383
EGAD00001000202 Neuroblastoma samples (Analyses_vcf files) 204 vcf
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
EGAD00000000017 Cord blood control samples from Gambia 0
EGAD00000000018 Severe malaria cases from Gambia 0
EGAD00000000029 Aggregate results from a case-control study on stroke and ischemic stroke. 19,602
EGAD00001000262 OICR PANCREATIC CANCER DATASET 5 bam
EGAD00001000276 OICR PANCREATIC CANCER DATASET 2 10 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
EGAD00010000456 Leukemia samples using 450K DNA methylation 800
EGAD00001000395 Noninvasive Prenatal Molecular Karyotyping from Maternal Plasma 1 bam
EGAD00010000460 GENCORD2 DNA methylation 294
EGAD00001000623 This VCF contains the full sequence data post QC. This consists of 41,911 individuals. All polymorphic sites are present in this VCF. 41,911 vcf
EGAD00001000645 ICGC MMML-seq Data Freeze July 2013 whole genome sequencing 42 bam
EGAD00001000648 ICGC MMML-seq Data Freeze July 2013 transcriptome sequencing 31 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
EGAD00001000618 1204 Sardinian males 1,195 bam
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
EGAD00001000664 Whole Genome Seq: 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. Paired-end RNA sequencing reads were mapped to the hg19 assembly of the human reference genome using BWA. Each ChIP-seq library was sequenced with two complete lanes on the Illumina HiSeq 2500 in the 101-bases paired-end rapid mode and aligned to hg19 using bwa. This resulted in the following coverage values (genome-wide, after deduplication, including all uniquely mapping reads): GBM103 macroH2A1: 17x H3K36me3: 20x MB59 macroH2A1: 11x H3K36me3: 11x 7 bam
EGAD00001000691 Whole genome sequencing data from Illumina platform were generated using 10 human cancer cell lines and 2 primary tumor samples. Nine of these samples contained fragments of human papillomavirus (HPV). 12 bai,bam
EGAD00010000744 Subset 2 of osteoarthritis cases genotyped on Illumina 610k from the arcOGEN Consortium (http://www.arcogen.org.uk/) with consent for osteoarthritis studies only. 2,326
EGAD00010000702 SNP-chip genotyping data for one proband in the DDD study (Ref : Carvalho AJHG 2015) 0
EGAD00001000693 The genetic consequences of cellular transformation by Epstein-Barr-Virus were assessed by comparing whole genome sequences of the original genome (before transformation) and the genome after transformation. 2 bam,vcf
EGAD00001000660 Analysis .bam files from HiSeq sequencing of Australian ICGC PDAC study samples, submitted 20130826 353 bam
EGAD00001000650 ICGC MMML-seq Data Freeze July 2013 miRNA sequencing 52 bam
EGAD00001000717 Dataset of CageKid Tumor DNA samples 95 bam
EGAD00001000718 Dataset of CageKid Tumor RNA samples 91 bam
EGAD00001000719 Dataset of CageKid Normal RNA samples 45 bam
EGAD00001000709 Dataset of CageKid Blood DNA samples 95 bam
EGAD00001000714 102 bam
EGAD00001000720 Dataset of CageKid tumor-normal paired RNA samples 90 bam
EGAD00001001355 DDD DATAFREEZE 2013-12-18: 1133 trios - VCF files (Ref: DDD Nature 2015) 3,335 readme_file,tab,vcf
EGAD00001000743 These files contain a total of 20.4M SNVs and the complete information output by the GATK UnifiedGenotyper v1.4 on all 767 GoNL samples. These calls are not trio-aware and all genotypes were reported regardless of their quality. Both filtered and passing calls are reported in these files. Filtered calls include (1) calls failing our VQSR threshold and (2) calls in the GoNL inaccessible genome. 767 vcf
EGAD00001000744 The samples in this panel come from 250 families: 248 parents-child trios and 2 parent-child duos. As the children do not provide additional haplotypes or population information, they were excluded from the panel. The samples present in the release are composed of 248 couples, 2 single individuals and 1 sample composed from the 2 haplotypes from the duo's children transmitted by their missing parent. The composed sample is named gonl-220c_223c. The files contain a total of 18.9M SNVs and 1.1M INDELs in autosomal chromosomes. They were generated by phasing/imputing the SNVs (a) and INDELs (b) using MVNCall. Only sites passing filters are reported. Sites filtered as part of the GoNL inaccessible genome were kept (but flagged as filtered) and still may contain true positive calls but should be used with care as they are located in parts of the genome that are less well captured (systematic under or over-covered or low-mapping quality) 499 vcf
EGAD00010000574 Pleuropulmonary blastoma samples using 250K 14
EGAD00001000777 Dataset contains MeDIP-Seq, MRE-Seq and H3K4me3 ChIP-Seq data on 5 GBM patients. 16 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
EGAD00001000816 ICGC medulloblastoma whole genome sequencing data, ICGC release 16 44 bam
EGAD00001000814 Whole genome alignments of DIPG patients 40 bam
EGAD00001000818 Quiescent Sox2+ cells drive hierarchical growth and relapse in Sonic hedgehog subgroup medulloblastoma 4 bam
EGAD00010000534 Illumina HumanMethylation450 BeadChip 0
EGAD00010000528 Illumina HumanHT-12 v4 array 0
EGAD00010000532 Illumina Human Omni1-Quad SNP genotyping array 0
EGAD00010000738 Generation Scotland APOE data 18,336
EGAD00001000789 UK10K_COHORT_ALSPAC REL-2012-06-02: Phenotype data 1,927 phenotype_file,readme_file
EGAD00001000790 UK10K_COHORT_TWINSUK REL-2012-06-02: Phenotype data 1,854 phenotype_file,readme_file
EGAD00010000554 SNP 6.0 arrays of small cell lung cancer 1,032
EGAD00010000556 SNP 6.0 arrays of small cell lung cancer 1,032
EGAD00010000298 All cases and controls (Hap300) 13,761
EGAD00010000296 1958BC control samples only (Hap550) 2,224
EGAD00010000294 1958BC control samples only (Hap300) 2,436
EGAD00010000292 All cases and Finnish, Dutch, Italian control samples (Hap300) 10,339
EGAD00010000290 NBS control samples only (Hap550) 2,276
EGAD00010000288 All cases and Finnish, Dutch, Italian control samples (Hap550) 6,313
EGAD00001000874 Indel/point mutation of chondrosarcoma 10 vcf
EGAD00001000781 Whole genome, high coverage, sequencing of 128 Ashkenazi Jewish controls 128 vcf
EGAD00010000566 HipSci normal samples using 500K 120
EGAD00010000564 HipSci normal samples using 47K 120
EGAD00010000568 HipSci normal samples using 450K 24
EGAD00010000570 Imputation-based meta-analysis of severe malaria in Kenya. 3,343
EGAD00010000572 Imputation-based meta-analysis of severe malaria in Gambia. 2,870
EGAD00010000580 Gencode control samples using 550K 217
EGAD00010000736 AAD case and control samples from UK and Norway 117
EGAD00010000578 Gencode case samples using 550K 249
EGAD00001000880 233 bam,vcf
EGAD00010000652 Genotyped samples using Illumina HumanOmni2.5 402
EGAD00010000698 PCGP INF ALL SNP6 0
EGAD00010000682 glioma samples tumor using 250K 762
EGAD00010000706 SNP array data for 668 cancer cell lines 0
EGAD00010000688 glioma normal samples using 250K 119
EGAD00010000684 glioma normal samples using cytoscan 3
EGAD00010000686 glioma samples tumor using cytoscan 5
EGAD00010000708 Human samples typed on Illumina Omni 5M 124
EGAD00010000704 610k genotyping imputed on Hapmap 3 and 1000G Phase 1 CEU 714
EGAD00001000158 Subgroup-specific structural variation across 1,000 medulloblastoma genomes 23 bam
EGAD00001001210 Altered translation response to stress by medulloblastoma-associated DDX3X mutations 28 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
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
EGAD00001001114 DDD DATAFREEZE 2013-12-18: 1133 trios - exome sequence BAM files (Ref: DDD Nature 2015) 3,335 bam,tab
EGAD00010000658 DLBCL 148 SNP 6.0 Cohort 148
EGAD00010000664 Finnish population cohort genotyping_B 340
EGAD00010000712 ATRT genotyping 0
EGAD00010000662 Finnish population cohort genotyping 7,803
EGAD00010000594 SCOOP severe early-onset obesity cases 1,720
EGAD00010000610 Samples from the Greek island of Crete, MANOLIS cohort 221
EGAD00010000596 PCGP Ph-likeALL GEA 837
EGAD00010000598 PCGP Ph-likeALL SNP6 1,724
EGAD00010000604 DNA methylation data using Illumina 450K 2,195
EGAD00001000946 Divergent clonal selection dominates medulloblastoma at recurrence 125 bam
EGAD00010000552 Neuroblastoma samples 130
EGAD00001001001 2 bam
EGAD00001000950 Whole genome sequencing data for ependymomas (5 tumor-control pairs). See Mack, Witt et al. Nature 506(7489):445-50, 2014 (PMID: 24553142). 10 bam
EGAD00001000951 Whole exome sequencing data for ependymomas (42 tumor-control pairs). See Mack, Witt et al. Nature 506(7489):445-50, 2014 (PMID: 24553142). 84 bam
EGAD00010000606 SNP6 data for matched normal samples 8
EGAD00010000608 SNP6 data for seminoma samples 8
EGAD00010000584 WTCCC2 Glaucoma samples using Illumina 670k array 2,765
EGAD00010000602 WTCCC2 Reading and Mathematics ability (RM) samples from UK using the Affymetrix 6.0 array 3,665
EGAD00010000612 Celiac disease North Indian samples using Immunochip 1,227
EGAD00001001887 Exome sequencing VCF files describing mutations during glioma progression. 82 vcf
EGAD00010000858 Achalasia cases & controls 8,151
EGAD00001001860 19 vcf
EGAD00010000616 HumanOmni1-Quad genotyping array 230
EGAD00010000618 Ischemic stroke cases 3,682
EGAD00010000620 Controls 3,683
EGAD00010000622 SNP array data for gastric cancer cell lines 30
EGAD00001001034 Whole genome data (Complete genomics platform) for the study EGAS00001000824 24 other
EGAD00001001038 We mapped the data to the UCSC human reference genome build 37 using BWA 0.5.9-r16. We first mapped each read pair separately using bwa aln. Then we used bwa sampe to map the paired reads together to a BAM9 file. The BAM file was then sorted by genomic position and indexed using PicardTools-1.32 SortSam. To prevent PCR artifacts from influencing the downstream analysis of our data, we used Picard to mark the duplicate reads, which were ignored in downstream analysis. We used GATK IndelRealigner on our data around known indels (from 1KG Pilot). The IndelRealigner creates all possible read alignments using the source and computes the likelihood of the data containing the indel based on the read pileup. Whenever the maximum likelihood contains an indel, the reads are realigned accordingly. Each base is associated with a phred-scaled base quality score. Calibration of Phred scores is crucial as they are used in some of the downstream analysis models. We used GATK to recalibrate the base qualities with respect to (i) the base cycle, (ii) original quality score, and (iii) dinucleotide context. To minimize issues stemming from mapping problems around indels, we decided to undergo a second round of indel realignment using the GATK IndelRealigner by family rather than by individual. For this second round, we considered two sources of possible indels: 1KG Phase 1 indels and indels aligned by BWA in the GoNL data. 769 bam
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
EGAD00010000630 The TEENAGE study target population comprised adolescent students aged 13–15 years attending the first three classes of public secondary schools located in the wider Athens area of Attica. 436
EGAD00010000634 WTCCC2 People of the British Isles (POBI) samples using Affymetrix 6.0 array 2,930
EGAD00010000632 WTCCC2 People of the British Isles (POBI) samples using Illumina 1.2M array 2,912
EGAD00010000628 The TEENAGE study target population comprised adolescent students aged 13–15 years attending the first three classes of public secondary schools located in the wider Athens area of Attica. 748
EGAD00010000642 CLL Expression Array 144
EGAD00010000644 Affymetrix SNP6.0 cancer cell line exome sequencing data 1,022
EGAD00010000646 DNA methylation analysis of 35 prostate tumor and 6 normal prostate samples 41
EGAD00010000648 nccRCC tumor/normal genotypes 81
EGAD00010000614 40 Druze Trios 120
EGAD00001000845 44 bam
EGAD00001001080 MDS patients 5 bam
EGAD00001001081 Healthy reference samples 3 bam
EGAD00001001303 The dataset for the PROP1 study consists of samples of patients with combined pituitary hormone deficiency due to two most prevalent mutations in the PROP1 gene (c.301_302delGA and c.150delA) and healthy relatives and controls. All subjects were genotyped for 21 single nucleotide polymorphisms surrounding the PROP1 gene in order to assess the potential ancestral origin of the respective mutations. The genotype data are displayed in the vcf format. 328 vcf
EGAD00001001329 28 bam
EGAD00010000718 BLUEPRINT Gene expression of different B-cell subpopulations 42
EGAD00010000716 BLUEPRINT DNA Methylation of different B-cell subpopulations 35
EGAD00001001075 miRNA-seq Cohort of 15 Benign Centroblasts 15 bam
EGAD00001001073 miRNA-seq Cohort of 140 Formalin Fixed Paraffin Embedded Diffuse Large B-cell Lymphoma Patient Samples 140 bam
EGAD00001001074 miRNA-seq Cohort of 92 Fresh Frozen Diffuse Large B-cell Lymphoma Patient Samples 92 bam
EGAD00001001087 RNAseq BAM files for the Skin samples of the EUROBATS project. 672 bai,bam
EGAD00001001086 These analysis are the BAM files for the LCLs samples of the EUROBATS samples. 765 bai,bam
EGAD00001001088 RNAseq BAM files for the blood samples of the EUROBATS project 391 bai,bam
EGAD00001001089 RNAseq BAM files for the Fat samples of the EUROBATS project 685 bai,bam
EGAD00010000656 Case samples using SNP 6.0 Array 20
EGAD00010000654 Control samples using SNP 6.0 Arrays 10
EGAD00010000650 Genotypes from Omni2.5 chip 1,213
EGAD00010000847 Genotyping using Affymetrix SNP6.0 49
EGAD00010000666 Purified plasma cells from tonsil of Healthy donor 8
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
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
EGAD00001001126 340 other
EGAD00001000963 Exome sequencing of sporadic schwannomatosis patients 16 bam
EGAD00001000964 Low-coverage whole genome sequencing of sporadic schwannomatosis patients 16 bam
EGAD00001001218 10 bam
EGAD00001001217 15 bam
EGAD00010000694 HCC array for cnv 55
EGAD00010000771 HipSci normal samples REL-2015-04 135
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
EGAD00010000640 WTCCC2 Visceral Leishmaniasis samples from Sudanl using Illumina 670k 21
EGAD00010000638 WTCCC2 Visceral Leishmaniasis samples from Indial using Illumina 670k 97
EGAD00010000636 WTCCC2 Visceral Leishmaniasis samples from Brazil using Illumina 670k 119
EGAD00010000696 PCGP ETP ALL SNP6 0
EGAD00001001226 smRNA-Seq assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Canada as part of the International Human Epigenome Consortium. 28 bam
EGAD00001001228 Whole genome shotgun sequencing 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. 27 bam,vcf
EGAD00001001227 Strand-specific mRNA-Seq 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. 32 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
EGAD00001001240 VCF files of somatic variants from tumor-normal pairs of Asian lung cancer patients 30 vcf
EGAD00010000690 Genome-wide SNP genotyping of African rainforest hunter-gatherers and neighbouring agriculturalists by Illumina HumanOmniExpress 160
EGAD00010000692 Genome-wide DNA methylation epigenotyping of African rainforest hunter-gatherers and neighbouring agriculturalists by Illumina HumanMethylation450 372
EGAD00010000740 Osteoarthritis cases genotyped on Illumina HumanOmniExpress from the arcOGEN Consortium (http://www.arcogen.org.uk/) with broader consent. 674
EGAD00010000724 Pilot experiment on functional genomics in osteoarthritis (methyl) 0
EGAD00010000730 WTCCC2 Psychosis Endophenotype samples from UK, Germany, Holland, Spain and Australia using the Affymetrix 6.0 array 1
EGAD00001000656 FACS phenotype of 1629 Sardinian samples 1,629 phenotype_file
EGAD00010000710 ATRT genotyping blood 0
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
EGAD00010000722 Pilot experiment on functional genomics in osteoarthritis (coreex) 1
EGAD00010000764 Ovarian tumor samples using Illumina 0
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
EGAD00001001413 DDD DATAFREEZE 2013-12-18: 1133 trios - README, family trios, phenotypes, validated DNMs (Ref: DDD Nature 2015) 3,335 readme_file,tab
EGAD00001001360 The majority of neuroblastoma patients have tumors that initially respond to chemotherapy, but a large proportion of patients will experience therapy-resistant relapses. The molecular basis of this aggressive phenotype is unknown. Whole genome sequencing of 23 paired diagnostic and relapsed neuroblastomas showed clonal evolution from the diagnostic tumor with a median of 29 somatic mutations unique to the relapse sample. Eighteen of the 23 relapse tumors (78%) showed RAS-MAPK pathway mutations. Seven events were detected only in the relapse tumor while the others showed clonal enrichment. In neuroblastoma cell lines we also detected a high frequency of activating mutations in the RAS-MAPK pathway (11/18, 61%) and these lesions predicted for sensitivity to MEK inhibition in vitro and in vivo. Our findings provide a rationale for genetic characterization of relapse neuroblastoma and show that RAS-MAPK pathway mutations may function as a biomarker for new therapeutic approaches to refractory disease. 221 other,vcf
EGAD00010000768 Replication data for HipSci normal samples using both HumanCoreExome-12_v1 and HumanOmni2.5-8 BeadChips 0
EGAD00010000766 We have established a mechanism for the collection of postal DNA samples from consenting National Joint Registry for England and Wales (NJR) patients and have carried out genotyping genome-wide in 903 patients with the condition Developmental Dysplasia of the Hip (DDH) on the Illumina CoreExome array 903
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
EGAD00001001941 Variants derived from mapped whole transcriptome RNA-Seq data from 476 human samples of early stage urothelial carcinoma. 476
EGAD00010000791 Illumina HumanOmni2.5-8 BeadChip 1
EGAD00001000702 Complete set of bam files associated with study EGAS00001000622 190 bam
EGAD00010000787 Epigen-Brasil samples using HumanOmni2.5 6,487
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
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
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
EGAD00010000748 Genotyping using Illumina Human OmniExpress12v1.0 1
EGAD00001001492 RNA-Seq data for 4 megakaryocyte-erythroid progenitor cell 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_rnaseq_analysis_crg_20150820 4 fastq
EGAD00001001561 RNA-Seq data for 3 hematopoietic multipotent progenitor cell sample(s). 9 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_rnaseq_analysis_crg_20150820 3 fastq
EGAD00001001534 RNA-Seq data for 5 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 23 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_rnaseq_analysis_crg_20150820 5 fastq
EGAD00001001558 RNA-Seq data for 5 common lymphoid progenitor sample(s). 20 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_rnaseq_analysis_crg_20150820 5 fastq
EGAD00001001501 RNA-Seq data for 3 granulocyte monocyte progenitor cell 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_rnaseq_analysis_crg_20150820 3 fastq
EGAD00001001550 RNA-Seq data for 7 erythroblast sample(s). 29 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_rnaseq_analysis_crg_20150820 7 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
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
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
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
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
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
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
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
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
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
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
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
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
EGAD00001001520 RNA-Seq data for 3 mature neutrophil - G-CSF/Dex. Treatment (16-20 hrs) 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_rnaseq_analysis_crg_20150820 3 fastq
EGAD00001001555 RNA-Seq data for 7 Acute promyelocytic leukemia 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_rnaseq_analysis_crg_20150820 7 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
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
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
EGAD00001001480 RNA-Seq 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_rnaseq_analysis_crg_20150820 3 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
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
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
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
EGAD00001001540 RNA-Seq data for 1 conventional dendritic 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_rnaseq_analysis_crg_20150820 1 fastq
EGAD00001001526 RNA-Seq data for 1 effector memory CD4-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_rnaseq_analysis_crg_20150820 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
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
EGAD00001001477 RNA-Seq data for 3 neutrophilic myelocyte 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_rnaseq_analysis_crg_20150820 3 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
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
EGAD00001001474 RNA-Seq data for 14 mature neutrophil 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_rnaseq_analysis_crg_20150820 14 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
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
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
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
EGAD00001001469 RNA-Seq data for 1 T-cell acute 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_rnaseq_analysis_crg_20150820 1 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
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
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
EGAD00001001483 RNA-Seq data for 1 CD3-negative, CD4-positive, CD8-positive, double positive thymocyte 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_rnaseq_analysis_crg_20150820 1 fastq
EGAD00001001586 RNA-Seq data for 4 alternatively activated macrophage sample(s). 6 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_rnaseq_analysis_crg_20150820 4 fastq
EGAD00001001582 RNA-Seq data for 18 macrophage sample(s). 19 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_rnaseq_analysis_crg_20150820 18 fastq
EGAD00001001504 RNA-Seq data for 3 band form neutrophil 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_rnaseq_analysis_crg_20150820 3 fastq
EGAD00001001500 RNA-Seq data for 2 CD38-negative naive B cell 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_rnaseq_analysis_crg_20150820 2 fastq
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
EGAD00001001506 RNA-Seq data for 8 CD14-positive, CD16-negative classical monocyte sample(s). 8 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_rnaseq_analysis_crg_20150820 8 fastq
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
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
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
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
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
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
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
EGAD00001001572 RNA-Seq data for 4 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_rnaseq_analysis_crg_20150820 4 fastq
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
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
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
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
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
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
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
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
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
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
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
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
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
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
EGAD00001001471 RNA-Seq data for 11 Multiple myeloma 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_rnaseq_analysis_crg_20150820 11 fastq
EGAD00001001456 1000Genomes imputed data set of 581 cases and 417 controls for male-pattern baldness 1 vcf
EGAD00010000819 Summary statistics from meta-analysis for BP phenotypes 0
EGAD00001001609 Maternal Plasma RNA Sequencing for Genomewide Transcriptomic Profiling and Identification of Pregnancy-Associated Transcripts 14 bam
EGAD00001001616 2 bam
EGAD00001001614 26 bam
EGAD00001001613 10 bam
EGAD00001001615 10 bam
EGAD00010000829 Illumina Infinium 450K array data 70
EGAD00010000827 Illumina Infinium 450K array data 1
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
EGAD00001001635 Whole genome sequencing detected structural rearrangements of TERT in 17/75 high stage neuroblastoma with 5 cases resulting from chromothripsis. Rearrangements were associated with increased TERT expression and targeted immediate up- and down-stream regions of TERT, placing in 7 cases a super-enhancer close to the breakpoints. TERT rearrangements (23%), ATRX deletions (11%) and MYCN amplifications (37%) identify three almost non-overlapping groups of high stage neuroblastoma, each associated with very poor prognosis. This submission contains all newly sequenced samples only. study_refcenter AMC 42 other
EGAD00001001660 Whole exome sequencing was performed to explore the mutational landscape and potential molecular signature of HPV-positive versus HPV-negative OAC. Four hr-HPV-positive and 8 HPV-negative treatment-naive fresh-frozen OAC tissue specimens and matched normal tissue were analysed to identify somatic genomic mutations 24 bam
EGAD00001001661 Genotype and exome data for an Australian Aboriginal population: a reference panel for health-based research. 72 vcf
EGAD00001002247 The Genetics of Type 2 Diabetes Consortium (GoT2D) is a collaboration between the University of Michigan, the Broad Institute and the Wellcome Trust Centre for Human Genetics. The overall aim is to extend upon recent efforts, such as genome-wide association studies (GWAS) and large scale meta-analyses. While they have proved successful at mapping genomic loci that influence human diseases, like type 2 diabetes, much of the heritability remains unexplained. In this study, we use next generation sequencing and genotyping technologies to query for lower frequency variants in the human genome. Thereby, allowing a deeper characterization of the spectrum of alleles associated with type 2 diabetes risk, and a better assessment of the genes that play a role in the etiology of type 2 diabetes development.  We studied 1,326 T2D cases and 1,331 normoglycemic controls from Northern and Central Europe (Sweden, Finland, UK, and Germany).  To efficiently characterize the entire genome sequence of each individual, we performed low-coverage (~5x) whole-genome sequencing, augmented by deep coverage (~100x) sequencing of the exome, and dense (2.5M) single nucleotide polymorphism (SNP) genotyping using the HumanOmni2.5 array.  The data deposited in EGA will include all the Swedish, Finnish, UK, and German samples. 2,872
EGAD00001002246 The Genetics of Type 2 Diabetes Consortium (GoT2D) is a collaboration between the University of Michigan, the Broad Institute and the Wellcome Trust Centre for Human Genetics. The overall aim is to extend upon recent efforts, such as genome-wide association studies (GWAS) and large scale meta-analyses. While they have proved successful at mapping genomic loci that influence human diseases, like type 2 diabetes, much of the heritability remains unexplained. In this study, we use next generation sequencing and genotyping technologies to query for lower frequency variants in the human genome. Thereby, allowing a deeper characterization of the spectrum of alleles associated with type 2 diabetes risk, and a better assessment of the genes that play a role in the etiology of type 2 diabetes development.  We studied 1,326 T2D cases and 1,331 normoglycemic controls from Northern and Central Europe (Sweden, Finland, UK, and Germany).  To efficiently characterize the entire genome sequence of each individual, we performed low-coverage (~5x) whole-genome sequencing, augmented by deep coverage (~100x) sequencing of the exome, and dense (2.5M) single nucleotide polymorphism (SNP) genotyping using the HumanOmni2.5 array.  The data deposited in EGA will include all the Swedish, Finnish, UK, and German samples. 13,007
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
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
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
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
EGAD00001001623 BBMRI - BIOS project - Freeze 1 - Bam files 2,117 bam,contig_fasta
EGAD00001001848 DDD DATAFREEZE 2014-11-04: 4293 trios - VCF files 12,539 vcf
EGAD00001001925 1461 Neuropathological and clinically characterised cases from the MRC Brain Bank 1,461 vcf
EGAD00001001854 Exome sequencing of nine PCC/PGL tumors, SF and FFPE samples 18 bam
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
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
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
EGAD00010000872 Genotyped case and control sampes using HumanExome Beadchip 1,610
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
EGAD00010000871 CLL and normal B cell samples using 450K 226
EGAD00001001899 HDAC and PI3K Antagonists Cooperate to Inhibit Growth of MYC-driven Medulloblastoma 102 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
EGAD00001001305 Dataset contains WES data from 3 astrocytoma patients: blood as control, primary tumor and recurrent tumor 9 bam
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
EGAD00001002001 Mapped data (bam files) for high-throughput whole genome sequence data for 83 modern Aboriginal Australians 83 bai,bam
EGAD00001002016 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: LICA-FR. 12
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
EGAD00001002011 RNA sequencing data of whole blood samples from smoking and non-smoking mothers and their children at gestation/birth and follow-up years. 64
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
EGAD00001002012 ChIPseq data of whole blood samples from smoking and non-smoking mothers and their children at gestation/birth and follow-up years. 16
EGAD00001002005 Using whole exome sequencing (WES), we identified homozygosity for a missense variant, VPS11: c.2536T>G (p.C846G), as the genetic cause of a leukoencephalopathy syndrome in two individuals from two unrelated Ashkenazi Jewish (AJ) families. Both patients exhibited highly concordant disease progression characterized by infantile onset leukoencephalopathy with brain white matter abnormalities, severe motor impairment, cortical blindness, intellectual disability, and seizures. 2
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
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
EGAD00001002037 Genome sequence data from an adrenal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study 2
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
EGAD00001002046 Genome and transcriptome sequence data from a liposarcoma 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
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
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
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
EGAD00001002126 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PRAD-UK. 116
EGAD00001002120 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: ORCA-IN. 26
EGAD00001002123 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: MALY-DE. 202
EGAD00001002121 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: BTCA-SG. 24
EGAD00001002129 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: BRCA-EU. 158
EGAD00001002154 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PAEN-AU. 98
EGAD00001002155 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: LIRI-JP. 524
EGAD00001002157 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: MELA-AU. 140
EGAD00001002156 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: ESAD-UK. 198
EGAD00001002132 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PACA-AU. 192
EGAD00001002122 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: BRCA-UK. 90
EGAD00001002119 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: LAML-KR. 18
EGAD00001002130 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: CLLE-ES. 194
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
EGAD00001002124 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: EOPC-DE. 113
EGAD00001002153 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PAEN-IT. 74
EGAD00001002125 ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: BOCA-UK. 148
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
EGAD00001002109 TSACP TruSeq Amplicon Panel dataset for the TraIT cell line use case 5
EGAD00001002069 Complete genomics data for VCaP and PC346c. 2
EGAD00001002071 qDNAseq shallow sequencing dataset of the cell line use case. 5
EGAD00010000230 WTCCC2 samples from Hypertension Cohort - Illuminus 2,943
EGAD00010000232 WTCCC2 samples from Type 2 Diabetes Cohort - Illuminus 2,975
EGAD00010000236 WTCCC2 samples from Coronary Artery Disease Cohort - Illuminus, GenoSNP 3,125
EGAD00010000385 MRCA sample using 300K Illumina 300K - GenomeStudio 394
EGAD00010000150 WTCCC2 project samples from Ankylosing spondylitis Cohort Illumina_670k - Illuminus 2,005
EGAD00001000150 Targeted re-sequencing of 97 genes in T-ALL 454 GS FLX Titanium 33 sff
EGAD00001000224 Enrichment of CRC 454 GS FLX Titanium; 2 bam
EGAD00001000225 Deep sequencing of KRAS 454 GS FLX Titanium; 8 fastq
EGAD00001000708 AZIN1 amplicon sequencing data of the EGAS00001000495 project. 454 GS FLX Titanium; 69 fastq
EGAD00001000272 Genomic Alterations in Gingivo-buccal Cancer: ICGC-India Project_YR01 454 GS FLX Titanium;, Illumina HiSeq 2000; 200 bam
EGAD00001000220 Deep sequencing of CTCs 454 GS FLX Titanium;, Illumina MiSeq; 3 bam
EGAD00001000888 NSCLC WGS. AB 5500 Genetic Analyzer; 4 bam
EGAD00001001436 AB 5500 Genetic Analyzer; 4 bam
EGAD00001001012 The need for a detailed catalogue of local variability for the study of rare diseases within the context of the Medical Genome Project motivated the whole exome sequencing of 267 unrelated individuals, representative of the healthy Spanish population. AB 5500xl Genetic Analyzer; 267 fastq
EGAD00001001596 Whole Exome Sequencing data from the germline of the patient as well as the tumors in bone marrow (T-ALL), Liver (Histiocytic Sarcoma) and ileum (non-Langerhans Cell Histiocytosis). AB 5500xl Genetic Analyzer; 4 bam
EGAD00001000096 Pancreatic adenocarcinoma QCMG 20120201 AB SOLiD 4 System 166 bam
EGAD00001000632 AB SOLiD 4 System; 12 SOLiD_native_csfasta,SOLiD_native_qual,bam
EGAD00001000680 Single end short-read (50 bp) SOLiD 4 sequencing data for 300 individuals, constituting 100 patient-parent trios. For more details please read; http://www.nejm.org/doi/full/10.1056/NEJMoa1206524 AB SOLiD 4 System; 300 bam
EGAD00001000779 AB SOLiD 4 System; 2 bam
EGAD00001001209 To examined the reproducibility of nucleotide variant calls in replicate sequencing experiments of the same genomic DNA, we performed targeted sequencing of all known human protein kinase genes (kinome) (~3.3 Mb) using the SOLiD v4 platform. This data set contains 17 breast cancer samples that were sequenced in duplicate (n=14) or triplicate (n=3), in order to assess concordance of all calls and single nucleotide variant (SNV) calls. AB SOLiD 4 System; 37 SOLiD_native_csfasta,SOLiD_native_qual
EGAD00001000293 Sequencing data for Australian Ovarian Cancer study submitted 20121116 AB SOLiD 4 System; 72 bam
EGAD00001001385 Exome sequencing in 3 Möbius patients AB SOLiD 4 System; 3
EGAD00001000323 Sequencing data for Australian Pancreatic Cancer study submitted 20130102 AB SOLiD 4 System;, Illumina HiSeq 2000; 200 bam
EGAD00001000049 Pancreatic adenocarcinoma QCMG 20110901 AB SOLiD System 3.0, AB SOLiD 4 System 26 bam,fastq
EGAD00001000201 MDACC-endo AB SOLiD System 3.0; 28 bam
EGAD00001000115 Mutational landscapes of primary triple negative breast cancers - WGS ABI_SOLID 32 bam
EGAD00010000262 WTCCC2 project Schizophrenia (SP) samples Affyemtrix 6.0 - CHIAMO 3,019
EGAD00010000526 SNP 6.0 arrays of small cell lung cancer Affymetrics_SNP_6.0- 63
EGAD00010000546 SNP 6.0 arrays of carcinoid samples Affymetrics_SNP_6.0- 74
EGAD00010000544 Cusihg's syndrome tumor samples using 250K Affymetrix 250K Nsp-GTYPE 16
EGAD00010000542 Cusihg's syndrome normal samples using 250K Affymetrix 250K Nsp-GTYPE 16
EGAD00010000714 aplastic anemia samples tumor using 250K Affymetrix 250K Nsp-GTYPE 440
EGAD00000000037 NcOEDG Stockholm 2 samples Affymetrix 5.0 514
EGAD00000000004 WTCCC1 project Coronary Artery Disease (CAD) samples Affymetrix 500K 1,998
EGAD00000000009 WTCCC1 project Type 2 Diabetes (T2D) samples Affymetrix 500K 1,999
EGAD00000000005 WTCCC1 project Inflammatory Bowel Disease (IBD) samples Affymetrix 500K 2,005
EGAD00000000007 WTCCC1 project Rheumatooid arthritis (RA) samples Affymetrix 500K 1,999
EGAD00000000001 WTCCC1 project samples from 1958 British Birth Cohort Affymetrix 500K 1,504
EGAD00000000006 WTCCC1 project Hypertension (HT) samples Affymetrix 500K 2,001
EGAD00000000003 WTCCC1 project Bipolar Disorder (BD) samples Affymetrix 500K 1,998
EGAD00000000008 WTCCC1 project Type 1 Diabetes (T1D) samples Affymetrix 500K 2,000
EGAD00000000002 WTCCC1 project samples from UK National Blood Service Affymetrix 500K 1,500
EGAD00000000036 NcOEDG Stockholm 1 samples Affymetrix 500K 484
EGAD00000000039 NcOEDG Malmo - Lund samples Affymetrix 500K 1,374
EGAD00000000016 WTCCC project Tuberculosis (TB) samples Affymetrix 500K 1,498
EGAD00000000015 WTCCC project African control samples Affymetrix 500K 1,496
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
EGAD00000000023 WTCCC2 project samples from National Blood Donors (NBS) Cohort Affymetrix 6.0 3,000
EGAD00000000021 WTCCC2 project samples from 1958 British Birth Cohort Affymetrix 6.0 3,000
EGAD00000000025 WTCCC2 project Ulcerative Colitis (UC) samples Affymetrix 6.0 2,869
EGAD00000000119 Genotypes from cell lines derived from breast carcinoma tissue Affymetrix 6.0 51
EGAD00000000047 Signal data for from 3 recurrent and 1 ovarian primary Granulosa Cell Tumour samples Affymetrix 6.0 4
EGAD00010000950 WTCCC2 Bacteraemia Susceptibility (BS) smaples using Affymetrix 6.0 Affymetrix 6.0 4,924
EGAD00010000282 Pharmacogenomic response to Statins samples (Genotypes/Phenotypes) Affymetrix 6.0 - CHIAMO 4,134
EGAD00010000490 Affymetrix Genome-Wide Human SNP Array 6.0 data Affymetrix 6.0- 19
EGAD00010000238 CLL Expression array Affymetrix GeneChip Human Genome U133 plus 2.0 64
EGAD00010000901 Russian Tuberculosis samples using Affymetrix 6.0 Affymetrix Genome-Wide Human SNP Array 6.0 Genotypes 11,937
EGAD00010000886 samples using Affymetrix HG_U133_+2 Affymetrix HG_U133_+2 99
EGAD00010000280 CLL Expression array Affymetrix snp 6.0 4
EGAD00010000266 Metabric breast cancer samples (Genotype raw data) Affymetrix SNP 6.0 543
EGAD00010000215 Segmented (CBS) copy number aberrations (CNA); validation set Affymetrix SNP 6.0 995
EGAD00010000217 Segmented (HMM) copy number aberrations (CNA); discovery set Affymetrix SNP 6.0 997
EGAD00010000213 Segmented (CBS) copy number aberrations (CNA); discovery set Affymetrix SNP 6.0 997
EGAD00010000216 Segmented (CBS) copy number variants (CNV); validation set Affymetrix SNP 6.0 995
EGAD00010000164 Affymetrix 6.0 CEL files Affymetrix SNP 6.0 1,992
EGAD00010000214 Segmented (CBS) copy number variants (CNV); discovery set Affymetrix SNP 6.0 997
EGAD00010000050 Matched tumor-negative pancreas tissues Affymetrix SNP 6.0 15
EGAD00010000051 Cell line derived from microdissected primary pancreatic ductal adenocarcinoma tissues Affymetrix SNP 6.0 15
EGAD00010000158 Affymetrix 6.0 cel files Affymetrix SNP 6.0 1,001
EGAD00010000558 SNP 6.0 arrays of small cell lung cancer Affymetrix SNP 6.0 54
EGAD00010000942 Breast lesions assayed with Affymetrix SNP 6.0 Affymetrix SNP 6.0 125
EGAD00010000915 Affymetrix SNP6.0 breast cancer genome sequencing data Affymetrix SNP6.0 344
EGAD00010000252 CLL Expression Arrays Affymetrix U219 137
EGAD00010000472 CLL Expression Array Affymetrix U219 219
EGAD00010000875 CLL Expression Array Affymetrix U219 1,008
EGAD00010000096 DBA case samples using 250K Nsp Affymetrix_250K(Nsp) - gtype 27
EGAD00010000480 ccRCC case samples using 250K Nsp Affymetrix_250K(Nsp) - gtype 240
EGAD00010000484 ccRCC control samples using 250K Nsp Affymetrix_250K(Nsp) - gtype 234
EGAD00010000419 Han Chinese samples using Affymetrix (cases) Affymetrix_6.0 62
EGAD00010000421 Han Chinese samples using Affymetrix (controls) Affymetrix_6.0 187
EGAD00010000148 tumour samples using Affymetrix Genome-Wide SNP6.0 arrays Affymetrix_GenomeWide_SNP6.34 104
EGAD00010000452 Chondrosarcoma case sample genotype using Affymetrix SNP6.0 Affymetrix_SNP6 36
EGAD00010000395 Myeloma case sample genotype using Affymetrix SNP6.0 Affymetrix_SNP6 19
EGAD00010000488 Chondroblastoma case sample genotype using Affymetrix SNP6.0 Affymetrix_SNP6- 7
EGAD00010000498 Affymetrix SNP6.0 genotype data for prostate cancer patients Affymetrix_SNP6- 18
EGAD00010000442 Affymetrix SNP 6.0 CEL files Affymetrix_SNP6_raw 1,302
EGAD00010000502 Case samples using SNP Array 6.0 Affymetrix_U133plus2- 35
EGAD00010000504 Control samples using SNP Array 6.0 Affymetrix_U133plus2- 35
EGAD00010000500 Case samples using U133 Plus 2.0 Array Affymetrix_U133plus2- 35
EGAD00010000462 SJLGG Case samples using Gene Expression Array Affymetrix_U133v2 75
EGAD00010000486 ccRCC case samples using expression array Agilent Human Whole Genome 4x44k v2 - Feature Extraction 101
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
EGAD00010000438 Normalized miRNA expression data Agilent ncRNA 60k 1,480
EGAD00010000444 Agilent ncRNA 60k txt files Agilent ncRNA 60k 1,480
EGAD00010000881 Digital images of ovarian cancer sections Aperio 91
EGAD00010000270 Metabric breast cancer samples (Images) Aperio image - H&E stained tissue_section 564
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
EGAD00001000139 Tumor sample of a serious ovarian carcinoma Complete Genomics 1 CompleteGenomics_native
EGAD00001000140 Blood sample of serious ovarian carcinoma patient Complete Genomics 1 CompleteGenomics_native
EGAD00001000060 Acral melanoma study whole genomes Complete Genomics 3 CompleteGenomics_native
EGAD00010000220 Ovarian & matched normal (Genotypes) Complete Genomics - CG Build 1.4.2.8 2
EGAD00001000196 Neuroblastoma samples Complete Genomics; 203 CompleteGenomics_native
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
EGAD00001000174 DATA_SET_Coverage_bias_sensitivity_of_variant_calling_for_4_WG_seq_tech Complete Genomics;, unspecified; 4 bam
EGAD00010000052 Monozygotic twins that are discordant for schizophrenia (Genotyping) CompleteGenomics build 1.4.2.8 - CG Build 1.4.2.8 36
EGAD00001000048 monozygotic twin discordant for schizophrenia CompleteGenomics build 1.4.2.8 - CG Build 1.4.2.8 2 CompleteGenomics_native
EGAD00010000921 samples using Affymetrix CYTOSCANHD CYTOSCANHD 12
EGAD00000000031 HLA genotyping of 1958 British Birth Cohort samples Dynal RELI SSO assay 6,662
EGAD00010000514 Case samples using SNP 6.0 Array GenomeWideSNP_6-BirdseedV2 12
EGAD00010000510 Matched control samples using HumanOmni1-Quad GenomeWideSNP_6-BirdseedV2 12
EGAD00010000512 Case samples using HumanOmni1-Quad GenomeWideSNP_6-BirdseedV2 12
EGAD00010000508 Matched control samples using SNP 6.0 Array GenomeWideSNP_6-BirdseedV2 12
EGAD00010000470 CLL Expression Array GPL570 20
EGAD00010000425 Han Chinese samples using Immunochip HanChinese_Immunochip 192
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
EGAD00001001266 Whole genome sequencing of primary angiosarcoma HiSeq X Ten; 12 cram
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
EGAD00001001271 Around 50 samples of pre-invasive lung cancer lesions showing subsequent clinical and pathological progression or regression HiSeq X Ten; 50 cram
EGAD00001001346 PREDICT/Predicting individual response and resistance to VEGFR/mTOR pathway therapeutic intervention using biomarkers discovered through tumour functional genomics. HiSeq X Ten; 164 cram
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
EGAD00001001890 This study is to look at the effect of Myc and oxygen conditions on mutational signatures, to help establish causative roles for particular signatures. HiSeq X Ten; 9 cram
EGAD00001001897 15x whole genome sequencing in samples from the Cretan Greek isolate collection HELIC MANOLIS HiSeq X Ten; 1,482 cram
EGAD00001001898 The study will investigate serial samples from the same patient taken at the time of MGUS or SMM diagnosis, and later at the time of evolution towards MM. Samples will be sequenced by whole genome along with a matched normal to obtain the highest possible amount of information toinvestigate genomic changes at disease evolution. HiSeq X Ten; 131 cram
EGAD00001001429 Profiling subclonal architecture and phylogeny in tumors by whole-genome sequence data mining and single-cell genome sequencing HiSeq X Ten; 2 cram
EGAD00001001929 This study is to look at mutational signatures in a haploid iPS lines carrying frame-shift mutations in DNA repair genes. This will help establish causative roles for particular signatures. HiSeq X Ten; 81 cram
EGAD00001001440 This project entailed generation of high depth WGS (30x) of 100 individuals from the general Greek population. HiSeq X Ten; 100 cram
EGAD00001001447 Whole genome sequencing of single cell derived organoids from normal colon tissue and colorectal cancer. HiSeq X Ten; 19 cram
EGAD00001001458 Whole genome sequencing of EBV-transformed B cells in order to determine whether EBV induction of activation-induced cytidine deaminase (AID) produces genome-wide mutations and/or chromosomal rearrangements. HiSeq X Ten; 12 cram
EGAD00001001659 Genome-wide analysis of mutations induced by ionizing radiation in human cells in different conditions. HiSeq X Ten; 12 cram
EGAD00001001629 Whole-genome somatic rearrangement and point mutation analysis in cell lines with induced telomere fusions. HiSeq X Ten; 20 cram
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
EGAD00001001855 This study is interested in lineage tracing of the adrenal gland. It will aid our understanding of phylogenetic relationships and contrasting mutational signatures between multiple functional and non-functional adrenal tumours and geographically sampled adrenal tissue. HiSeq X Ten; 15 cram
EGAD00001001634 This dataset includes the whole genomes, sequenced to high depth (30x) of 25 individuals from Papua New Guinea. The individuals were chosen from several geographically distinct Papuan groups, focusing on the highland regions: Bundi, Kundiawa, Mendi, Marawaka and Tari. HiSeq X Ten; 25
EGAD00001001995 Whole genome sequencing (30X) using Hiseq X TEN on 4 HCC cell lines, primary HCCs and early-passage PDCs. HiSeq X Ten; 12
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
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
EGAD00001002146 The Chinese University of Hong Kong Hereditary Spastic Paraplegia Data HiSeq X Ten; 4
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
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
EGAD00001002198 This set of samples is composed of eight young people (7-16 years old) that have developed melanoma with first-degree relatives that have also developed cancer, which suggests a genetic component to their disease. Here we want to sequence these samples in order to find the causative mutations. As these samples do not carry any of the high-penetrance mutations known to date, finding the genes(s) responsible will offer new insights into the genetic mechanisms underlying predisposition to melanoma. HiSeq X Ten;, Illumina HiSeq 2000; 7
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
EGAD00000000120 WTCCC2 project Multiple Sclerosis (MS) samples Human670-QuadCustom v1 11,375
EGAD00010000516 Samples from the Pomak Villages in Greece, Pomak isolate HumanExome_12v1.1_A -GenCall, zCall 1,046
EGAD00010000518 Samples from the Greek island of Crete, MANOLIS cohort HumanExome_12v1.1_A -GenCall, zCall 1,280
EGAD00010000377 DNA methylation analysis of 6 primary lymphoma samples HumanMethylation450k Bead Chip - Genome Studio 6
EGAD00010000379 DNA methylation analysis of 2 peripheral blood samples HumanMethylation450k Bead Chip - Genome Studio 2
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
EGAD00010000908 Illumina SNP-arrays for matching retinoblastoma-blood pairs and retinoblastoma cell lines. HumanOmni1 Quad BeadChip 132
EGAD00010000919 samples using Illumina HUMANOMNI1QUAD HUMANOMNI1QUAD 2
EGAD00010000920 samples using Illumina HUMANOMNIEXPRESS HUMANOMNIEXPRESS 50
EGAD00010000522 Samples from the Greek island of Crete, MANOLIS cohort HumanOmniExpress-12 v1.1 BeadChip-GenCall 1,364
EGAD00010000940 Gambian specimens with trachomatous scarring WHO grade C2/C3 Illiumina Omni 2.5 1,531
EGAD00010000144 Healthy volunteer collection of European Ancestry Illumin OmniExpress v1.0 - Illumina GenomeStudio 288
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
EGAD00010000773 HipSci normal samples REL-2014-11 Illumina 580
EGAD00010000892 Healthy individuals from Italy Illumina 300
EGAD00010000909 HipSci normal ES lines REL-2016-04 Illumina 2
EGAD00010000775 HipSci normal samples REL-2014-11 Illumina 580
EGAD00010000910 HipSci normal ES lines REL-2016-04 Illumina 2
EGAD00010000911 HipSci normal ES lines REL-2016-04 Illumina 2
EGAD00010000284 NBS control samples only (Hap300) Illumina (Various) 2,500
EGAD00010000286 All cases and controls (Hap550) Illumina (various) 11,950
EGAD00000000024 WTCCC2 project samples from National Blood Donors (NBS) Cohort Illumina 1.2M 3,000
EGAD00000000022 WTCCC2 project samples from 1958 British Birth Cohort Illumina 1.2M 3,000
EGAD00010000383 MRCA sample using 100K Illumina 100K - GenomeStudio 394
EGAD00000000011 WTCCC1 project Autoimmune Thyroid Disease (ATD) samples Illumina 15K 900
EGAD00000000014 WTCCC1 project samples from 1958 British Birth Cohort Illumina 15K 1,504
EGAD00000000010 WTCCC1 project Ankylosing Spondylitis (AS) samples Illumina 15K 957
EGAD00000000012 WTCCC1 project Multiple Sclerosis (MS) samples Illumina 15K 975
EGAD00000000013 WTCCC1 project Breast cancer (BC) samples Illumina 15K 1,004
EGAD00010000951 SNP array data for 668 cancer cell lines Illumina 2.5M 668
EGAD00010000130 Cerebellar ataxia, mental retardation, and disequilibrium syndrome (CAMRQ) samples Illumina 300 Duo V2 - Bead Studio, Illumina 2
EGAD00010000381 MRCE sample using 300K Illumina 300K - GenomeStudio 543
EGAD00010000946 Human samples, 450k analysis Illumina 450k 127
EGAD00010000916 BASIS breast cancer DNA methylation Illumina 450k Illumina 450k 457
EGAD00010000464 Down syndrome SNP genotyping data Illumina 550K - Illumina Genome Studio 338
EGAD00000000104 Gabriel samples from the Russian UFA cohort Illumina 610-Quad 0
EGAD00000000098 Gabriel samples from the Swiss SALPADIA cohort Illumina 610-Quad 0
EGAD00000000090 Gabriel samples from the Russian KMSU cohort Illumina 610-Quad 0
EGAD00000000105 Gabriel samples from the multicenter occupational cohort Illumina 610-Quad 0
EGAD00000000087 Gabriel samples from the multicenter GAIN cohort Illumina 610-Quad 0
EGAD00000000092 Gabriel samples from the German MAGIS cohort Illumina 610-Quad 0
EGAD00000000083 Gabriel samples from the French EGEA Cohort Illumina 610-Quad 0
EGAD00000000088 Gabriel samples from the Karelia Allergy Study Illumina 610-Quad 0
EGAD00000000076 Gabriel samples from the Australian Bussleton Cohort Illumina 610-Quad 0
EGAD00000000095 Gabriel samples from the Dutch PIAMA cohort Illumina 610-Quad 0
EGAD00000000093 Gabriel samples from the German MAGIS cohort Illumina 610-Quad 0
EGAD00000000082 Gabriel samples from the French EGEA Cohort Illumina 610-Quad 0
EGAD00000000102 Gabriel samples from the Russian TOMSK cohort Illumina 610-Quad 0
EGAD00000000106 Gabriel samples from the multicenter occupational cohort Illumina 610-Quad 0
EGAD00000000085 Gabriel samples from the German Gabriel Advanced Survey Illumina 610-Quad 0
EGAD00000000108 Gabriel samples from the UK AUGOSA cohort Illumina 610-Quad 0
EGAD00000000075 Gabriel samples from the Swedish BAMSE Cohort Illumina 610-Quad 0
EGAD00000000107 Gabriel samples from the multicenter occupational cohort Illumina 610-Quad 0
EGAD00000000091 Gabriel samples from the Russian KMSU cohort Illumina 610-Quad 0
EGAD00000000101 Gabriel samples from the Russian TOMSK cohort Illumina 610-Quad 0
EGAD00000000074 Gabriel samples from the Swedish BAMSE Cohort Illumina 610-Quad 0
EGAD00000000103 Gabriel samples from the Russian UFA cohort Illumina 610-Quad 0
EGAD00000000086 Gabriel samples from the multicenter GAIN cohort Illumina 610-Quad 0
EGAD00000000077 Gabriel samples from the Australian Bussleton Cohort Illumina 610-Quad 0
EGAD00000000097 Gabriel samples from the Swiss SALPADIA cohort Illumina 610-Quad 0
EGAD00000000110 Gabriel aggregate data from the asthma study samples Illumina 610-Quad 0
EGAD00000000084 Gabriel samples from the German Gabriel Advanced Survey Illumina 610-Quad 0
EGAD00000000089 Gabriel samples from the Karelia Allergy Study 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
EGAD00000000073 Gabriel samples from the 1958 British Birth Cohort Illumina 610-Quad 0
EGAD00000000096 Gabriel samples from the Dutch PIAMA cohort Illumina 610-Quad 0
EGAD00000000026 Randomly-selected, unrelated individuals Illumina 610-Quad 518
EGAD00010000912 SEA 610K Illumina 610K 1
EGAD00000000057 WTCCC project samples from the Parkinson's disase cohort Illumina 610K Quad 1,705
EGAD00000000056 WTCCC project samples from the primary biliary cirrhosis cohort Illumina 610K Quad 1,705
EGAD00000000060 Samples from the UK Glomerulonephritis DNA bank Illumina 610K Quad, Illumina Hap300 1,705
EGAD00010000913 SEA 660K Illumina 660K 3
EGAD00000000035 NcOEDG Helsinki 4 samples Illumina CNV370 693
EGAD00000000115 Summary data from GWAS analysis on 856 cases and 2836 control Illumina CytoSNP-12 3,719
EGAD00001000100 Renal Matched Pair Cell Line Exome Sequencing Illumina Genome Analyzer II 10 bam
EGAD00001000026 Investigation of the genetic basis of the rare syndrome Post-Transfusion Purpura (PTP) Illumina Genome Analyzer II 5 bam,srf
EGAD00001000094 Cancer Genome Libraries Tests Illumina Genome Analyzer II 16 bam
EGAD00001000003 Gencode Exome Pilot Illumina Genome Analyzer II 7 srf
EGAD00001000092 Cancer Exome Resequencing Illumina Genome Analyzer II 58 bam
EGAD00001000104 Acute Lymphoblastic Leukemia Exome sequencing 2 Illumina Genome Analyzer II 97 bam
EGAD00001000095 Acute Myeloid Leukemia Sequencing Illumina Genome Analyzer II 9 bam
EGAD00001000089 Acute Lymphoblastic Leukemia Exome sequencing Illumina Genome Analyzer II 20 bam
EGAD00001000018 Identifying causative mutations for Thrombocytopenia with Absent Radii Illumina Genome Analyzer II 5 bam
EGAD00001000024 Whole Exome Sequencing for Characterization of Disease Causing Mutations in two Pakistani Families Suffering from Autosomal Recessive Ocular Disorders. Illumina Genome Analyzer II 4 srf
EGAD00001000111 CML Discovery Project Illumina Genome Analyzer II 6 bam
EGAD00001000029 Grey Platelet Syndrome (GPS) Illumina Genome Analyzer II 5 srf
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
EGAD00001000040 Bleeding Illumina Genome Analyzer II 6 bam
EGAD00001000058 Exome Sequencing analysis Illumina Genome Analyzer II 21 Illumina_native_qseq
EGAD00001000057 RNA-Seq analysis Illumina Genome Analyzer II 15 Illumina_native_qseq
EGAD00001000063 Triple Negative Breast Cancer sequencing Illumina Genome Analyzer II 6 bam
EGAD00000000053 Sequencing data from Breast Cancer samples Illumina Genome Analyzer II 1
EGAD00001000102 Myeloproliferative Disorder Sequencing Illumina Genome Analyzer II 6 bam
EGAD00001000098 FRCC Exome sequencing Illumina Genome Analyzer II 16 bam
EGAD00001000034 "Usage of small amounts of DNA for Illumina sequencing" Illumina Genome Analyzer II 3 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
EGAD00001000036 "Copy number variant detection in multiple foci of three prostate cancer tumors" Illumina Genome Analyzer II 9 bam
EGAD00000000051 Sequencing data from matching Renal Carcinoma samples Illumina Genome Analyzer II 25
EGAD00001000090 Glioma cell lines rearrangement screen Illumina Genome Analyzer II 3 bam
EGAD00000000114 Whole transcriptome sequence data from 18 ovarian clear-cell carcinoma samples and one TOV21G ovarian clear-cell carcinoma cell line Illumina Genome Analyzer II 1
EGAD00001000031 Human Colorectal Cancer Exome Sequencing Illumina Genome Analyzer II 16 srf
EGAD00001000038 Hyperfibrinolysis Illumina Genome Analyzer II 5 bam
EGAD00001000093 Breast Cancer Exome Resequencing Illumina Genome Analyzer II 21 bam
EGAD00001000091 Non Tumour Renal Cell Line Sequencing Illumina Genome Analyzer II 1 bam
EGAD00001000037 An evaluation of different strategies for large-scale pooled sequencing study design. Illumina Genome Analyzer II 7 bam,srf
EGAD00001000013 CLL Cancer Whole Genome Sequencing Illumina Genome Analyzer II 19 srf
EGAD00001000059 Screening for human epigenetic variation at CpG islands Illumina Genome Analyzer II 116 bam
EGAD00001000041 Various Platelet Disorders Illumina Genome Analyzer II 7 bam
EGAD00001000064 Cell Line Sub Clone Rearrangement Screen Illumina Genome Analyzer II 6 bam
EGAD00001000097 Matched breast cancer fusion gene study Illumina Genome Analyzer II 46 bam,srf
EGAD00001000066 Breast Cancer Follow Up Series Illumina Genome Analyzer II 288 bam
EGAD00001000105 MuTHER adipose tissue small RNA expression Illumina Genome Analyzer II 130 bam
EGAD00001000103 Myeloproliferative Disorder Sequencing Illumina Genome Analyzer II 4 bam
EGAD00001000019 Lethal malformation syndrome Illumina Genome Analyzer II 6 srf
EGAD00001000112 Identifying Novel Fusion Genes in Myeloma Illumina Genome Analyzer II 6 bam
EGAD00001000099 Meningioma Exome Illumina Genome Analyzer II 26 bam
EGAD00001000065 Mixed Leukemia Rearrangement Screen Illumina Genome Analyzer II 5 bam
EGAD00000000046 RNA-SEQ data from 3 recurrent and 1 ovarian primary Granulosa Cell Tumour samples Illumina Genome Analyzer II 4
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
EGAD00000000048 Sequencing data from oestrogen-receptor-alpha-positive metastatic lobular breast cancer sample Illumina Genome Analyzer II 1
EGAD00000000049 RNA-SEQ data from oestrogen-receptor-alpha-positive metastatic lobular breast cancer sample Illumina Genome Analyzer II 1
EGAD00001000088 ER-, HER2-, PR- breast Cancer genome sequencing Illumina Genome Analyzer II 6 bam
EGAD00000000052 Sequencing data from natching Pancreatic Carcinoma samples Illumina Genome Analyzer II 25
EGAD00001000025 Determination of the molecular nature of the Vel blood group by exome sequencing Illumina Genome Analyzer II 4 srf
EGAD00001000022 Exome sequencing in patients with cardiac arrhythmias Illumina Genome Analyzer II 20 srf
EGAD00001000050 Tandem duplication of chromosomal segments is common in ovarian and breast cancer genomes Illumina Genome Analyzer II 13 bam
EGAD00001000084 Matched Ovarian Cancer Sequencing Illumina Genome Analyzer II 23 bam
EGAD00001000004 CLL cancer Sample Sequencing Illumina Genome Analyzer II, Illumina Genome Analyzer 5 srf
EGAD00001000101 ADCC Exome Sequencing Illumina Genome Analyzer II, Illumina HiSeq 2000; 125 bam
EGAD00001000118 Osteosarcoma Exome Sequencing Illumina Genome Analyzer II, Illumina HiSeq 2000; 102 bam
EGAD00001000106 Primary Myelofibrosis Myeloproliferative Disease exome sequencing Illumina Genome Analyzer II, Illumina HiSeq 2000; 67 bam
EGAD00001000068 Multifocal Breast Project Illumina Genome Analyzer II, Illumina HiSeq 2000; 22 bam,srf
EGAD00001000045 Somatic mutation of SF3B1 in myelodysplasia with ring sideroblasts and other cancers Illumina Genome Analyzer II, Illumina HiSeq 2000; 33 bam,cram,srf
EGAD00001000212 Functional characterisation of CpG islands in human tissues Illumina Genome Analyzer II; 26 bam
EGAD00001000348 Exome sequencing of Bilateral Anophthalmia cases- Pilot Study Illumina Genome Analyzer II; 16 bam
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
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
EGAD00001000213 Screening for abnormal CGI methylation in primary colorectal tumours Illumina Genome Analyzer II; 21 bam
EGAD00001000052 UK10K_NEURO_MUIR REL-2011-01-28 Illumina Genome Analyzer II; 104 vcf
EGAD00001001453 The project is to evaluate the genomic binding sites of the histone demethylase JARID1C. This gene was recently identified in CGP as a novel recessive cancer gene in human renal cell carcinoma. Illumina Genome Analyzer II; 4 bam
EGAD00001000340 The objective of this study is to resequence of targeted intervals containing autosomal recessive variants causing neurological disorders in consanguineous pedigrees. Using homozygosity mapping, three intervals of very different sizes have previously been unambiguously mapped for three different neurological diseases: 2.4Mb, 8Mb and 14.3Mb in size, for Microlissencephaly, Severe Mental Retardation and Complicated hereditary spastic paraplegia respectively. This study is a pilot to assess how well custom targeted resequencing performs across a broad size range of intervals. The study design is to use a different custom capture probe set for each interval, pulldown from a single patient from each family, and sequence 1 lane using Illumina paired-reads for each sample. Candidate variants will be followed up in the families themselves, and in patients with similar phenotypes from outbred populations Illumina Genome Analyzer II; 3 bam
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
EGAD00001000351 This pilot study aims to generate pilot data to inform future study designs by resequencing the whole exomes of 10 unrelated individuals diagnosed with Congenital Heart Disease (CHD). Illumina Genome Analyzer II; 16 bam
EGAD00001000197 Progressive Hearing Loss Illumina Genome Analyzer II; 8 bam
EGAD00001000258 Deep RNA sequencing in CLL Illumina Genome Analyzer II; 107 fastq
EGAD00001000423 The aim is to find rare variants of intermediate penetrance in those at risk of Crohn's disease Illumina Genome Analyzer II; 10 bam
EGAD00001000398 The Cardiogenics re-sequencing study will consist of three parts: Eight pools of 25 individuals will be sequenced using a Nimblegen hybrid-capture solution specific to miRNA sequences, 80 pools of 25 individuals will be sequenced using a custom Agilent SureSelect array covering genes associated with coronary artery disease (CAD) and myocardial infarction (MI), 10 individuals from families with a history of CAD/MI will be exome sequenced using the Sanger exome array. The experiment will use the early onset patients from the German MI cohort and the UK BHF CAD/MI cohort both of which have strong family history. For controls we will consider individuals from the UKBS and KORA cohorts. Illumina Genome Analyzer II; 8 bam
EGAD00001000636 The ETV6-RUNX1 fusion gene, found in 25% of childhood acute lymphoblastic leukemia (ALL), is acquired in utero but requires additional somatic mutations for overt leukemia. We used exome and low-coverage whole-genome sequencing to characterize the critical secondary events associated with leukemic transformation. RAG-mediated deletions emerge as the dominant mutational process, accounting for at least 43% of genomic rearrangements and characterized by the presence of recombination signal sequence motifs near the breakpoints; incorporation of non-templated sequence at the junction and a ten-fold enrichment at promoters and enhancers of genes actively transcribed in early B-lineage development. Single-cell tracking shows that this mechanism is not restricted to one founder cell but is rather active throughout leukemic evolution. Integration of point mutation and rearrangement data identifies recurrent inactivation of ATF7IP and MGA as two new tumor suppressor genes.Thus, a remarkably parsimonious mutational process transforms ETV6-RUNX1 lymphoblasts, striking promoters and enhancers of the genes that normally control B-cell differentiation. Illumina Genome Analyzer II; 117 bam
EGAD00001000758 dataset for BGI bladder cancer project Illumina Genome Analyzer II; 198 fastq
EGAD00001001443 Illumina Genome Analyzer II; 199 fastq
EGAD00001001626 RNA-Seq Illumina GAII dataset for the TraIT cell-line use case (added reverse and forward reads). Illumina Genome Analyzer II; 6 bam,fastq
EGAD00001001645 Illumina Genome Analyzer II; 28
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
EGAD00001000005 Various Cancer Fusion Gene Sequencing Illumina Genome Analyzer II;, Illumina Genome Analyzer II 14 bam,srf
EGAD00001000007 Osteosarcoma Sequencing Illumina Genome Analyzer II;, Illumina Genome Analyzer II 43 bam,srf
EGAD00001000083 Recurrent Somatic Mutations in CLL Illumina Genome Analyzer II;, Illumina Genome Analyzer IIx 61 fastq
EGAD00001001269 Exome bam files of 75 Individuals From Multiply Affected Coeliac Families Illumina Genome Analyzer II;, Illumina Genome Analyzer IIx; 75 bam
EGAD00001000380 Illumina paired-end sequencing of whole- exome pulldown DNA from Severe Insulin Resistant patients. Illumina Genome Analyzer II;, Illumina HiSeq 2000; 64 bam
EGAD00001000295 UK10K_RARE_HYPERCHOL REL-2012-11-27 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 120 vcf
EGAD00001000186 UK10K_RARE_HYPERCHOL REL-2012-02-22 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 71 vcf
EGAD00001000167 UK10K_RARE_HYPERCHOL REL-2012-01-13 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 48 vcf
EGAD00001000207 UK10K_RARE_HYPERCHOL REL-2012-07-05 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 88 vcf
EGAD00001000178 UK10K_RARE_CHD REL-2012-01-13 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 46 vcf
EGAD00001000294 UK10K_RARE_CHD REL-2012-11-27 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 124 vcf
EGAD00001000210 UK10K_RARE_CHD REL-2012-07-05 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 124 vcf
EGAD00001000192 UK10K_RARE_CHD REL-2012-02-22 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 46 vcf
EGAD00001000342 This project aims to find causal variants in 50 patients diagnosed with Microcephalic Osteodysplastic Primordial Dwarfism (MOPD), of presumed recessive inheritance performing whole exome sequencing to ~50x mean depth. This is a collaboration with Prof A. Jackson, MRC Human Genetics Unit, Edinburgh Illumina Genome Analyzer II;, Illumina HiSeq 2000; 66 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
EGAD00001000307 UK10K_RARE_COLOBOMA REL-2012-11-27 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 117 vcf
EGAD00001000206 UK10K_RARE_COLOBOMA REL-2012-07-05 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 123 vcf
EGAD00001000179 UK10K_RARE_COLOBOMA REL-2012-01-13 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 75 vcf
EGAD00001000185 UK10K_RARE_COLOBOMA REL-2012-02-22 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 98 vcf
EGAD00001000152 UK10K_RARE_THYROID REL-2012-01-13 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 27 vcf
EGAD00001000208 UK10K_RARE_THYROID REL-2012-07-05 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 65 vcf
EGAD00001000187 UK10K_RARE_THYROID REL-2012-02-22 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 65 vcf
EGAD00001000329 UK10K_RARE_THYROID REL-2012-11-27 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 113 vcf
EGAD00001000297 UK10K_RARE_FIND REL-2012-11-27 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 124 vcf
EGAD00001000171 UK10K_RARE_FIND REL-2012-01-13 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 44 vcf
EGAD00001000209 UK10K_RARE_FIND REL-2012-07-05 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 121 vcf
EGAD00001000190 UK10K_RARE_FIND REL-2012-02-22 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 90 vcf
EGAD00001000322 UK10K_NEURO_MUIR REL-2012-11-27 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 166 vcf
EGAD00001000170 UK10K_NEURO_MUIR REL-2012-01-13 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 167 vcf
EGAD00001000236 EGAD00001000236_UK10K_NEURO_MUIR_REL_2012_07_05 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 167 vcf
EGAD00001000339 Multiple myeloma is an incurable plasma cell malignancy whose molecular pathogenesis is incompletely understood. We used whole exome sequencing, copy number profiling and cytogenetic to analyses 84 samples from 67 patients with myeloma. In addition to known myeloma genes, we identify new candidate genes, including truncations of SP140, ROBO1 and FAT3 and clustered missense mutations in EGR1. We find oncogenic mutations in cancer genes not previously implicated in myeloma, including SF3B1, PI3KCA and PTEN. We define diverse processes contributing to the mutational repertoire, including kataegis and somatic hypermutation. Most cases have at least one cluster of subclonal variants, including subclonal driver mutations, implying on-going tumor evolution. Serial samples revealed diverse patterns of clonal evolution, including linear evolution, differential clonal response and branching evolution. Our findings reveal the myeloma genome to be heterogeneous across patients and, within individual patients, to exhibit diversity in clonal admixture and dynamics in response to therapy. Illumina Genome Analyzer II;, Illumina HiSeq 2000; 154 bam,srf
EGAD00001000194 UK10K_COHORT_TWINS REL-2011-12-01 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 1,713 vcf
EGAD00001000188 UK10K_RARE_SIR REL-2012-02-22 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 63 vcf
EGAD00001000334 UK10K_RARE_SIR REL-2012-11-27 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 111 vcf
EGAD00001000218 UK10K_RARE_SIR REL-2012-07-05 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 81 vcf
EGAD00001000153 UK10K_RARE_SIR REL-2012-01-13 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 38 vcf
EGAD00001000191 UK10K_RARE_CILIOPATHIES REL-2012-02-22 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 128 vcf
EGAD00001000296 UK10K_RARE_CILIOPATHIES REL-2012-11-27 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 108 vcf
EGAD00001000168 UK10K_RARE_CILIOPATHIES REL-2012-01-13 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 50 vcf
EGAD00001000217 UK10K_RARE_CILIOPATHIES REL-2012-07-05 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 150 vcf
EGAD00001000198 Gene Discovery in Age-Related Hearing Loss Illumina Genome Analyzer II;, Illumina HiSeq 2000; 20 bam
EGAD00001000417 UK10K_RARE_HYPERCHOL REL-2013-04-20 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 125 vcf
EGAD00001000413 UK10K_RARE_CHD REL-2013-04-20 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 125 vcf
EGAD00001000415 UK10K_RARE_COLOBOMA REL-2013-04-20 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 123 vcf
EGAD00001000416 UK10K_RARE_FIND REL-2013-04-20 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 124 vcf
EGAD00001000420 UK10K_RARE_THYROID REL-2013-04-20 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 124 vcf
EGAD00001000419 UK10K_RARE_SIR REL-2013-04-20 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 121 vcf
EGAD00001000414 UK10K_RARE_CILIOPATHIES REL-2013-04-20 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 122 vcf
EGAD00001000425 GENCORD2 RNA-seq BAM files using BWA Illumina Genome Analyzer II;, Illumina HiSeq 2000; 568 bam
EGAD00001000443 UK10K_NEURO_MUIR REL-2013-04-20 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 175 vcf
EGAD00001000424 The aim of this project is to identify rare variants in the 1q region associated with type 2 diabetes. To this end 651 case samples and 651 control samples from six populations have been pooled (pool sizes range from 27-33 individuals), and are being sequenced. The hybridization solution being used captures the exons and UTRs of genes in the 1q region. Illumina Genome Analyzer II;, Illumina HiSeq 2000; 23 bam
EGAD00001000635 The ETV6-RUNX1 fusion gene, found in 25% of childhood acute lymphoblastic leukemia (ALL), is acquired in utero but requires additional somatic mutations for overt leukemia. We used exome and low-coverage whole-genome sequencing to characterize the critical secondary events associated with leukemic transformation. RAG-mediated deletions emerge as the dominant mutational process, accounting for at least 43% of genomic rearrangements and characterized by the presence of recombination signal sequence motifs near the breakpoints; incorporation of non-templated sequence at the junction and a ten-fold enrichment at promoters and enhancers of genes actively transcribed in early B-lineage development. Single-cell tracking shows that this mechanism is not restricted to one founder cell but is rather active throughout leukemic evolution. Integration of point mutation and rearrangement data identifies recurrent inactivation of ATF7IP and MGA as two new tumor suppressor genes.Thus, a remarkably parsimonious mutational process transforms ETV6-RUNX1 lymphoblasts, striking promoters and enhancers of the genes that normally control B-cell differentiation. Illumina Genome Analyzer II;, Illumina HiSeq 2000; 50 bam,srf
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
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
EGAD00001000285 We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses. Illumina Genome Analyzer II;, Illumina HiSeq 2000; 55 bam
EGAD00001000741 UK10K_COHORT_TWINSUK REL-2012-06-02: Low-coverage whole genome sequencing; variant calling, genotype calling and phasing Illumina Genome Analyzer II;, Illumina HiSeq 2000; 1,854 readme_file,tabix,vcf,vcf_aggregate
EGAD00001001398 We sequenced 205 patients who were suffering NSCLC with Exome sequencing method. Illumina Genome Analyzer II;, Illumina HiSeq 2000; 147 fastq
EGAD00001001397 We sequenced 292 patients who were suffering NSCLC with Whole genome sequencing or Exome sequencing method. Illumina Genome Analyzer II;, Illumina HiSeq 2000; 72 fastq
EGAD00001001335 We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses. Illumina Genome Analyzer II;, Illumina HiSeq 2000; 28
EGAD00001002237 The disordered transcriptomes of cancer encompass direct effects of somatic mutation on transcription; co-ordinated secondary alterations in transcriptional pathways; and increased transcriptional noise. To catalogue the rules governing how somatic mutation Overall, 59% of 6980 exonic substitutions were expressed. Compared to other classes, nonsense mutations showed lower expression levels than expected with patterns characteristic of nonsense-mediated decay. 14% of 4234 genomic rearrangements caused transcriptional abnormalities, including exon skips, exon reusage, fusion transcripts and premature poly-adenylation. We found productive, stable transcription from sense-to-antisense gene fusions and gene-to-intergenic rearrangements, suggesting that these mutation classes may drive more transcriptional disruption than previously suspected. Systematic integration of transcriptome with genome data therefore reveals the rules by which transcriptional machinery interprets somatic mutation. Illumina Genome Analyzer II;, Illumina HiSeq 2000; 59
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
EGAD00001000023 Recurrent Somatic Mutations in CLL Illumina Genome Analyzer IIx 11 fastq
EGAD00001000044 Recurrent Somatic Mutations in CLL Illumina Genome Analyzer IIx 212 fastq
EGAD00001000032 Hepatitis C IL28B pooled resequencing study with 100 responders and 100 non-responders Illumina Genome Analyzer IIx 4 Illumina_native
EGAD00001000042 Whole-Exome-Seq-Dataset Illumina Genome Analyzer IIx 30 bam
EGAD00001000043 RNA-Seq-Dataset Illumina Genome Analyzer IIx 16 bam
EGAD00001000061 Acral melanoma study whole exomes Illumina Genome Analyzer IIx 3 fastq
EGAD00001000132 Mutational landscapes of primary triple negative breast cancers - RNA seq Illumina Genome Analyzer IIx, Illumina Genome Analyzer IIx; 80 bam
EGAD00001000113 Mutational landscapes of primary triple negative breast cancers - Exomes Illumina Genome Analyzer IIx, Illumina Genome Analyzer IIx; 108 bam
EGAD00001000279 ICGC MMML-seq Data Freeze November 2012 whole exome sequencing Illumina Genome Analyzer IIx; 4 bam
EGAD00001000177 Whole Genome Methylation in CLL Illumina Genome Analyzer IIx; 6 fastq
EGAD00001000303 ICGC prostate cancer whole genome mate-pair sequencing Illumina Genome Analyzer IIx; 22 bam
EGAD00001000733 The dataset entails 48 RRBS libraries of 24 siblings. 24 individuals are conceived during the Dutch Famine, a severe 6 month famine at the end of World War 2. A same sex sibling was added as a control, allowing partial matching for (early) familial environment and genetics. Illumina Genome Analyzer IIx; 48 bam
EGAD00001000703 SCLC - Whole genome sequencing data Publication Peifer et al., 2012, Nature Genetics Illumina Genome Analyzer IIx; 29 bam
EGAD00001001263 Unaligned bam of 31 samples derived from blood Illumina Genome Analyzer IIx; 31 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
EGAD00001001108 MMP-seq tumor samples (FASTQ) Illumina Genome Analyzer IIx; 218 fastq
EGAD00001001107 MMP-seq cell lines (FASTQ) Illumina Genome Analyzer IIx; 154 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
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
EGAD00001000642 Illumina HiScanSQ; 2 bam
EGAD00001000643 Illumina HiScanSQ; 2 bam
EGAD00001002112 RNA-seq data from 195 pediatric BCP-ALL cases. Alignment: TopHat 2.0.7. Reference genome: hg19. Illumina HiScanSQ; 195
EGAD00001001220 Illumina HiSeq 1000; 10 bam
EGAD00001001091 We established and validated a sequence capture based NGS testing approach for PKD1. The presence of six PKD1 pseudogenes and tremendous allelic heterogeneity make molecular genetic testing of PKD1 variants challenging. In the publication accompaying this dataset (An efficient and comprehensive strategy for genetic diagnostics of polycystic kidney disease, Eisenberger et.al., PLoS one), we demonstrate that the applied standard mapping algorithm specifically aligns reads to the PKD1 locus and overcomes the complication of unspecific capture of pseudogenes. This dataset contains the raw PKD1 reads of all patients from the publication. Illumina HiSeq 1500; 55 fastq
EGAD00001000160 DATA FILES FOR SJACT Illumina HiSeq 2000 16 bam
EGAD00001000081 Splenic Marginal Zone Lymphoma with villous lymphocytes exome sequencing Illumina HiSeq 2000 1 bam
EGAD00001000075 Gastric and Esophageal tumour rearrangement screen Illumina HiSeq 2000 32 bam
EGAD00001000165 DATA FILES FOR SJINF Illumina HiSeq 2000 46 bam
EGAD00001000085 Somatic Histone H3 mutations Illumina HiSeq 2000 14 bam
EGAD00001000087 An exome sequencing pilot study of HIV elite-long term non progressors and rapid progressors Illumina HiSeq 2000 25 bam
EGAD00001000072 Fanconi Anemia transformation to AML Illumina HiSeq 2000 6 bam
EGAD00001000149 A Comprehensive Catalogue of Somatic Mutations from a Human Cancer Genome Illumina HiSeq 2000 2 srf
EGAD00001000053 Exome sequencing in patients with Calcific Aortic Valve Stenosis Illumina HiSeq 2000 20 bam
EGAD00001000159 DATA FILES FOR SJOS Illumina HiSeq 2000 37 bam
EGAD00001000109 Unraveling the genetic basis of a collagen migration defect in patients with a combined platelet dysfunction and reduced bone density Illumina HiSeq 2000 29 bam
EGAD00001000163 DATA FILES FOR SJPHALL Illumina HiSeq 2000 18 bam
EGAD00001000054 Mutational Screening of Human Acute Myleloid Leukaemia Samples Illumina HiSeq 2000 10 bam
EGAD00001000131 Genetic landscape of hepatocellular carcinoma Illumina HiSeq 2000 48 bam
EGAD00001000136 CML blast phase rearrangement screen Illumina HiSeq 2000 6 bam
EGAD00001000069 Lung Rearrangement Study Illumina HiSeq 2000 48 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
EGAD00001000077 CRLF2 sequencing project Exomes Illumina HiSeq 2000 26 bam
EGAD00001000162 DATA FILES FOR SJEPD Illumina HiSeq 2000 44 bam
EGAD00001000135 Neuroblastoma whole genome sequencing Illumina HiSeq 2000 80 bam
EGAD00001000076 CRLF2 sequencing project Illumina HiSeq 2000 13 bam
EGAD00001000121 Breast Cancer Whole Genome Sequencing Illumina HiSeq 2000 6 bam
EGAD00001000161 DATA FILES FOR SJLGG Illumina HiSeq 2000 33 bam
EGAD00001000071 Kaposi sarcoma exome Illumina HiSeq 2000 20 bam
EGAD00001000133 The landscape of cancer genes and mutational processes in breast cancer Illumina HiSeq 2000, Illumina Genome Analyzer II 199 bam
EGAD00001000017 PAS Pedigrees: Identification of novel genetic variants contributing to cardiovascular disease in pedigrees with premature atherosclerosis. Illumina HiSeq 2000, Illumina Genome Analyzer II 18 bam,srf
EGAD00001000110 Breast Cancer Exome Sequencing Illumina HiSeq 2000, Illumina Genome Analyzer II 179 bam
EGAD00001000154 Single-cell genome sequencing reveals DNA-mutation per cell cycle Illumina HiSeq 2000, Illumina Genome Analyzer II 12 bam,srf
EGAD00001000039 Platelet collagen defect Illumina HiSeq 2000, Illumina Genome Analyzer II 11 bam
EGAD00001000074 Integrative Oncogenomics of Multiple Myeloma Illumina HiSeq 2000, Illumina Genome Analyzer II 174 bam,srf
EGAD00001000107 SCAT osteosarcoma sequencing Illumina HiSeq 2000, Illumina Genome Analyzer II 114 bam
EGAD00001000062 ADCC Rearrangement Screen Illumina HiSeq 2000, Illumina Genome Analyzer II 14 bam,srf
EGAD00001000082 20 Matched Pair Breast Cancer Genomes Illumina HiSeq 2000, Illumina Genome Analyzer II 42 bam
EGAD00001000138 The expression data for this study can be found here: http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-1088/ and its SNP6 data can be found here: http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-1087/ Illumina HiSeq 2000, Illumina Genome Analyzer II 58 bam,srf
EGAD00001000119 Chordoma Exome Sequencing Illumina HiSeq 2000, Illumina Genome Analyzer II, Illumina HiSeq 2000; 50 bam
EGAD00001000123 Polycythemia Vera Myeloproliferative Disease exome sequencing Illumina HiSeq 2000, Illumina Genome Analyzer II, Illumina HiSeq 2000; 119 bam,srf
EGAD00001000021 Paroxysmal neurological disorders Illumina HiSeq 2000, Illumina Genome Analyzer II, Illumina HiSeq 2000; 97 bam,srf
EGAD00001000108 Paroxysmal neurological disorders Illumina HiSeq 2000, Illumina Genome Analyzer II, Illumina HiSeq 2000; 327 bam,srf
EGAD00001000117 Myelodysplastic Syndrome Exome Sequencing Illumina HiSeq 2000, Illumina Genome Analyzer II, Illumina HiSeq 2000; 152 bam,srf
EGAD00001000116 Acute Lymphoblastic Leukemia Sequencing Illumina HiSeq 2000, Illumina Genome Analyzer II, Illumina HiSeq 2000; 61 bam,srf
EGAD00001000015 Exome sequencing of hyperplastic polyposis patients. Illumina HiSeq 2000, Illumina Genome Analyzer II, Illumina HiSeq 2000; 84 bam,srf
EGAD00001000016 Familial Melanoma Sequencing Illumina HiSeq 2000, Illumina Genome Analyzer II, Illumina HiSeq 2000; 89
EGAD00001000046 Gastric Cancer Exome Sequencing Illumina HiSeq 2000, Illumina Genome Analyzer IIx 43 fastq
EGAD00001000027 ICGC Germany PedBrain Medulloblastoma Pilot_2_LM Illumina HiSeq 2000, Illumina Genome Analyzer IIx 8 bam
EGAD00001000122 DATA_SET_ICGC_PedBrainTumor_Medulloblastoma Illumina HiSeq 2000, Illumina Genome Analyzer IIx 206 bam
EGAD00001000128 Familial Thrombocytosis germline exome sequencing Illumina HiSeq 2000, Illumina HiSeq 2000; 4 bam
EGAD00001000070 TMD_AMLK Exome Study Illumina HiSeq 2000, Illumina HiSeq 2000; 50 bam,cram
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
EGAD00001000127 Burden of Disease in Sarcoma Illumina HiSeq 2000, Illumina HiSeq 2000; 220 bam,cram
EGAD00001000145 Matched Pair Cancer Cell line Whole Genomes Illumina HiSeq 2000, Illumina HiSeq 2000; 58 bam
EGAD00001000130 Breast Cancer Matched Pair Cell Line Whole Genomes Illumina HiSeq 2000, Illumina HiSeq 2000; 22 bam
EGAD00001000144 Lung Cancer Whole Genomes Illumina HiSeq 2000, Illumina HiSeq 2000; 18 bam
EGAD00001000067 Cancer Single Cell Sequencing Illumina HiSeq 2000, Illumina HiSeq 2000; 16 bam,srf
EGAD00001000129 Essential Thrombocythemia Myeloproliferative Disease exome sequencing Illumina HiSeq 2000, Illumina HiSeq 2000; 189 bam
EGAD00001000125 Chondrosarcoma Exome Illumina HiSeq 2000, Illumina HiSeq 2000; 104 bam
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
EGAD00001000078 ALK inhibitors in the context of ALK-dependent cancer cell lines Illumina HiSeq 2000, Illumina HiSeq 2000; 16 bam,cram
EGAD00001000142 Renal Follow Up Series Illumina HiSeq 2000, Illumina HiSeq 2000; 637 bam
EGAD00001000126 HER2 positive Breast Cancer Illumina HiSeq 2000, Illumina HiSeq 2000; 101 bam,cram
EGAD00001000124 Sequencing Acute Myeloid Leukaemia Illumina HiSeq 2000, Illumina HiSeq 2000; 4 bam
EGAD00001000143 Xenograft Seqeuncing Illumina HiSeq 2000, Illumina HiSeq 2000; 16 bam
EGAD00001000079 PREDICT Illumina HiSeq 2000, Illumina HiSeq 2000; 186 bam,cram
EGAD00001000164 DATA FILES FOR SJRHB Illumina HiSeq 2000, Illumina HiSeq 2000; 29 bam
EGAD00001000055 Genetic variation in Kuusamo Illumina HiSeq 2000, Illumina HiSeq 2000; 434 vcf
EGAD00001000147 Osteosarcoma Whole Genome Illumina HiSeq 2000, Illumina HiSeq 2000; 108 bam,cram
EGAD00001000073 MDSMPN Rearrangement Screen Illumina HiSeq 2000, Illumina HiSeq 2000; 11 bam
EGAD00001000134 Sequence reads for pediatric GBM samples for manuscript: Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma Illumina HiSeq 2000, Illumina HiSeq 2500; 54 fastq
EGAD00001000227 EGAD00001000227_UK10K_NEURO_ABERDEEN_REL_2012_07_05 Illumina HiSeq 2000; 347 vcf
EGAD00001000315 UK10K_NEURO_ABERDEEN REL-2012-11-27 Illumina HiSeq 2000; 313 vcf
EGAD00001000271 Pilot study Pilocytic Astrocytoma ICGC PedBrain, whole genome sequencing of 5 tumors and matched blood Illumina HiSeq 2000; 10 bam
EGAD00001000887 Exome sequencing of Resistant BCC samples. Illumina HiSeq 2000; 23 fastq
EGAD00001000881 RNA sequencing of Resistant BCC samples. Illumina HiSeq 2000; 11 fastq
EGAD00001000269 OLD DATA FILES FOR SJMB - Superseded by EGAD00001001864 Illumina HiSeq 2000; 68 bam
EGAD00001000319 UK10K_NEURO_GURLING REL-2012-11-27 Illumina HiSeq 2000; 48 vcf
EGAD00001000237 EGAD00001000237_UK10K_NEURO_GURLING_REL_2012_07_05 Illumina HiSeq 2000; 43 vcf
EGAD00001000336 UK10K_OBESITY_SCOOP REL-2012-11-27 Illumina HiSeq 2000; 784 vcf
EGAD00001000241 EGAD00001000241_UK10K_OBESITY_SCOOP_REL_2012_07_05 Illumina HiSeq 2000; 674 vcf
EGAD00001000151 UK10K OBESITY REL-2011-07-14 Illumina HiSeq 2000; 88 vcf
EGAD00001000181 UK10K_OBESITY_SCOOP REL-2012-01-13 Illumina HiSeq 2000; 212 vcf
EGAD00001000193 UK10K_OBESITY_SCOOP REL-2012-02-22 Illumina HiSeq 2000; 573 vcf
EGAD00001000318 UK10K_NEURO_FSZ REL-2012-11-27 Illumina HiSeq 2000; 119 vcf
EGAD00001000184 UK10K_NEURO_FSZ_REL_2012_01_13 Illumina HiSeq 2000; 120 vcf
EGAD00001000240 UK10K_NEURO_FSZ_REL_2012_07_05 Illumina HiSeq 2000; 120 vcf
EGAD00001000215 RNA sequencing of colon tumor/normal sample pairs Illumina HiSeq 2000; 139 fastq
EGAD00001000216 Exome capture sequencing of colon tumor/normal pairs Illumina HiSeq 2000; 144 fastq
EGAD00001000214 Whole genome sequencing of colon samples Illumina HiSeq 2000; 11 fastq
EGAD00001000306 ICGC prostate cancer whole genome sequencing Illumina HiSeq 2000; 22 bam
EGAD00001000270 DATA_SET_EOP-PCA-LargeAndSmallTumors1 Illumina HiSeq 2000; 18 bam
EGAD00001000235 EGAD00001000235_UK10K_NEURO_IOP_COLLIER_REL_2012_07_05 Illumina HiSeq 2000; 170 vcf
EGAD00001000321 UK10K_NEURO_IOP_COLLIER REL-2012-11-27 Illumina HiSeq 2000; 158 vcf
EGAD00001002158 This is an in vitro genome-wide CRISPR/cas9 screen in human glioblastoma stem cells, screening for genes essential for survival of these cells. These cells express cas9 and have been transfected with a guide RNA library causing gene knockouts. We will analyse the sequencing data for depletion of guide RNAs. Illumina HiSeq 2000; 6
EGAD00001000345 Exome sequencing of 12 DNA samples obtained from patients with structural brain malformations. Illumina HiSeq 2000; 9 bam
EGAD00001000310 UK10K_NEURO_ASD_BIONED REL-2012-11-27 Illumina HiSeq 2000; 76 vcf
EGAD00001000228 EGAD00001000228_UK10K_NEURO_ASD_BIONED_REL_2012_07_05 Illumina HiSeq 2000; 59 vcf
EGAD00001001125 Exome sequencing of Untreated BCC samples. Illumina HiSeq 2000; 91 fastq
EGAD00001000261 Retinoblastoma whole genome sequencing Illumina HiSeq 2000; 8 bam
EGAD00001000256 UK10K_NEURO_UKSCZ REL-2012-07-05 Illumina HiSeq 2000; 595 vcf
EGAD00001000335 UK10K_NEURO_UKSCZ REL-2012-11-27 Illumina HiSeq 2000; 527 vcf
EGAD00001000182 UK10K_NEURO_UKSCZ REL-2012-01-13 Illumina HiSeq 2000; 95 vcf
EGAD00001000317 UK10K_NEURO_EDINBURGH REL-2012-11-27 Illumina HiSeq 2000; 214 vcf
EGAD00001000233 EGAD00001000233_UK10K_NEURO_EDINBURGH_REL_2012_07_05 Illumina HiSeq 2000; 219 vcf
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
EGAD00001000347 These samples include exome sequences of family members with dyslipidemias from Finnish origin. Illumina HiSeq 2000; 95 bam
EGAD00001001862 RNA-seq of PDXs Illumina HiSeq 2000; 12 fastq
EGAD00001001693 Fastq files of RNAseq of 182 samples of biliary tract cancer Illumina HiSeq 2000; 182 fastq
EGAD00001001872 Targeted exome sequencing of patient derived xenografts from primary colorectal tumours and liver metastases. Illumina HiSeq 2000; 333 cram
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
EGAD00001000390 We propose to definitively characterise the somatic genetics of triple negative breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses. Illumina HiSeq 2000; 101 bam,cram
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
EGAD00001000223 RNA sequencing of SCLC tumor/normal sample pairs and cell lines Illumina HiSeq 2000; 79 fastq
EGAD00001000222 Exome capture sequencing of SCLC tumor/normal pairs and cell lines Illumina HiSeq 2000; 103 fastq
EGAD00001000221 Whole genome sequencing of SCLC tumor/normal samples Illumina HiSeq 2000; 4 fastq
EGAD00001001053 DATA FILES FOR SJOS-WGS-2ndBatch Illumina HiSeq 2000; 27 bam
EGAD00001001052 DATA FILES FOR SJTALL Illumina HiSeq 2000; 24 bam
EGAD00001000259 DATA FILES FOR SJAMLM7 Illumina HiSeq 2000; 8 bam
EGAD00001000183 UK10K_NEURO_FSZNK REL-2012-01-13 Illumina HiSeq 2000; 273 vcf
EGAD00001000234 EGAD00001000234_UK10K_NEURO_FSZNK_REL_2012_07_05 Illumina HiSeq 2000; 281 vcf
EGAD00001000332 UK10K_NEURO_FSZNK REL-2012-11-27 Illumina HiSeq 2000; 258 vcf
EGAD00001000382 Whole Exome Sequencing of Permanent Neonatal Diabetes Patients Illumina HiSeq 2000; 25 bam
EGAD00001000232 EGAD00001000232_UK10K_NEURO_ASD_TAMPERE_REL_2012_07_05 Illumina HiSeq 2000; 54 vcf
EGAD00001000314 UK10K_NEURO_ASD_TAMPERE REL-2012-11-27 Illumina HiSeq 2000; 48 vcf
EGAD00001000343 This project aims to identify highly penetrant coding variants increasing the risk of Congenital Heart Disease (CHD) performing whole exome sequencing on DNA samples from 23 affected individuals, selected from 10 families with presumed Autosomal Recessive Inheritance. This is a collaboration with Prof. Eamonn Maher and Dr. Chirag Patel from the Department of Medical and Molecular Genetics, University of Birmingham plans to sequence 23 indexed Agilent whole exome pulldown libraries on 75Bp PE HiSeq (Illumina) Illumina HiSeq 2000; 24 bam
EGAD00001000249 This is the bam file generated after alignment using BWA program for the SAIF genome Illumina HiSeq 2000; 1 bam
EGAD00001000254 This dataset contain the raw files generated for SAIF genome project Illumina HiSeq 2000; 1 fastq
EGAD00001000381 Illumina paired-end sequencing of whole- exome pulldown DNA from Severe Insulin Resistant patients. Illumina HiSeq 2000; 3 bam
EGAD00001000602 Illumina HiSeq 2000; 1 bam
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
EGAD00001000229 EGAD00001000229_UK10K_NEURO_ASD_FI_REL_2012_07_05 Illumina HiSeq 2000; 85 vcf
EGAD00001000173 UK10K_NEURO_ASD_FI REL-2012-01-13 Illumina HiSeq 2000; 85 vcf
EGAD00001000311 UK10K_NEURO_ASD_FI REL-2012-11-27 Illumina HiSeq 2000; 84 vcf
EGAD00001000231 EGAD00001000231_UK10K_NEURO_ASD_SKUSE_REL_2012_07_05 Illumina HiSeq 2000; 320 vcf
EGAD00001000313 UK10K_NEURO_ASD_SKUSE REL-2012-11-27 Illumina HiSeq 2000; 305 vcf
EGAD00001000280 This experiment is to validate putative somatic substitutions and indels identified in an exome screen of ~50 osteosarcoma tumour/normal pairs. It is the first stage in our ICGC commitment to study osteosarcoma. The validation process is an important component of our analysis to clarify the data prior to looking for evidence of new cancer genes, or subverted pathways important in the development of cancer. 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; 112 bam
EGAD00001000278 ICGC MMML-seq Data Freeze November 2012 whole genome sequencing Illumina HiSeq 2000; 12 bam
EGAD00001000281 ICGC MMML-seq Data Freeze November 2012 transcriptome sequencing Illumina HiSeq 2000; 6 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
EGAD00001000298 UK10K_RARE_NEUROMUSCULAR REL-2012-11-27 Illumina HiSeq 2000; 130 vcf
EGAD00001000180 UK10K_RARE_NEUROMUSCULAR REL-2012-01-13 Illumina HiSeq 2000; 47 vcf
EGAD00001000189 UK10K_RARE_NEUROMUSCULAR REL-2012-02-22 Illumina HiSeq 2000; 86 vcf
EGAD00001000219 UK10K_RARE_NEUROMUSCULAR REL-2012-07-05 Illumina HiSeq 2000; 117 vcf
EGAD00001000274 DATA_SET_TRANSCIPTOME_Comparing_sequencing_four_proto-typical_Burkitt_lymphomas_BL_IG-MYC_translocation Illumina HiSeq 2000; 4 bam
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
EGAD00001000393 Illumina HiSeq 2000; 30 vcf
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
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
EGAD00001000320 UK10K_NEURO_IMGSAC REL-2012-11-27 Illumina HiSeq 2000; 111 vcf
EGAD00001000239 EGAD00001000239_UK10K_NEURO_IMGSAC_REL_2012_07_05 Illumina HiSeq 2000; 114 vcf
EGAD00001000653 This is a continuation of the Chordoma Sequencing Project. All cancers arise due to somatically acquired abnormalities in DNA sequence. Systematic sequencing of cancer genomes allows acquisition of complete catalogues of all classes of somatic mutation present in cancer. These mutation catalogues will allow identification of the somatically mutated cancer genes that are operative and characterise patterns of somatic mutation that may reflect previous exogenous and endogenous mutagenic exposures. In this application, we aim to perform whole genome sequencing on 10 chordoma matched genome pairs. RNA Sequencing/Methylation and SNP6 and an additional sequencing of three cancer cell lines will be added to this work. Illumina HiSeq 2000; 10 bam,cram
EGAD00001000268 DATA FILES FOR SJCBF Illumina HiSeq 2000; 34 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
EGAD00001000352 DATA FILES FOR SJLGG Illumina HiSeq 2000; 7 bam
EGAD00001000353 DATA FILES FOR SJLGG Illumina HiSeq 2000; 45 bam
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
EGAD00001000341 This pilot study aims to generate pilot data to inform future study designs in consanguineous families or inbred populations by resequencing the exome of six individuals from five families with neurodevelopmental diseases. For all of these families a single mapping interval containing the causal variant has previously been identified. Illumina HiSeq 2000; 6 bam
EGAD00001000299 Whole exome sequencing of samples selected from the Finrisk sample collection. The samples sequenced in this study have all been collected in Kuusamo, Finland. Illumina HiSeq 2000; 24 bam
EGAD00001000242 EGAD00001000242_UK10K_NEURO_ASD_MGAS_REL_2012_07_05 Illumina HiSeq 2000; 60 vcf
EGAD00001000312 UK10K_NEURO_ASD_MGAS REL-2012-11-27 Illumina HiSeq 2000; 96 vcf
EGAD00001000328 ICGC PedBrain: RNA sequencing Illumina HiSeq 2000; 28 fastq
EGAD00001000275 Data set for Whole-genome-Sequencing of adult medulloblastoma Illumina HiSeq 2000; 10 bam
EGAD00001000248 RNAseq Pulldown Illumina HiSeq 2000; 6 bam
EGAD00001000230 EGAD00001000230_UK10K_NEURO_ASD_GALLAGHER_REL_2012_07_05 Illumina HiSeq 2000; 72 vcf
EGAD00001000316 UK10K_NEURO_ASD_GALLAGHER REL-2012-11-27 Illumina HiSeq 2000; 75 vcf
EGAD00001000266 This Study uses a focused bespoke bait pull down library method to target findings of Osteosarcoma whole genome and whole exome sequencing studies in order to validate findings. This method will also be used on a larger set of tumour only samples in order to find precedence of these findings in a larger set of patient samples. Illumina HiSeq 2000; 110 bam
EGAD00001000203 Otosclerosis gene discovery Illumina HiSeq 2000; 10 bam
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
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
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
EGAD00001000369 We propose to definitively characterise the somatic genetics of a number of pediatric malignant tumours including ependymoma, high grade glioma and central nervous system primitive neurectodermal tumours through generation of comprehensive catalogues of somatic mutations by high coverage genome sequencing. Illumina HiSeq 2000; 3 bam
EGAD00001000273 This Study uses a focused bespoke bait pull down library method to target findings of Meningioma whole genome and whole exome sequencing studies in order to validate findings. This method will also be used on a larger set of tumour only samples in order to find precedence of these findings in a larger set of patient samples. Illumina HiSeq 2000; 147 bam
EGAD00001000246 Integrative Oncogenomics of multiple myeloma Illumina HiSeq 2000; 106 bam
EGAD00001000361 This is a small pilot data set to test the feasibility of cDNA exomes across 1200 cancer cell line panel. cDNA exomes or Fus-seq is further explained in this studies Abstract. Illumina HiSeq 2000; 3 bam
EGAD00001000255 Testing the feasibility of genome scale sequencing in routinely collected FFPE cancer specimens versus matched fresh frozen samples Illumina HiSeq 2000; 32 bam
EGAD00001000263 We propose to definitively characterise the somatic genetics of Prostate cancer through generation of comprehensive catalogues of somatic mutations by high coverage genome sequencing. See ICGC website for more information: http://icgc.org/icgc/cgp/70/508/71331 Illumina HiSeq 2000; 18 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
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
EGAD00001000354 Testing the feasibility 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; 81 bam
EGAD00001000386 Wholegenome libraries will be prepared from at least two serial samples reflecting different stages of disease progression and matched constitutional DNA for 30 Myelodysplastic syndrome patient samples. Five lanes of Illumina HiSeq sequencing will be performed on each of the tumour samples and four lanes for each of the constitutional DNA. Sequencing data will mapped to build 37 of the human reference genome and analysis will be performed to characterize the spectrum of somatic variation present in these samples including single base pair mutations, insertions, deletions as well as larger structural variants and genomic rearrangements. Illumina HiSeq 2000; 83 bam,cram
EGAD00001000267 This Study uses a focused bespoke bait pull down library method to target findings of Chordoma whole genome and whole exome sequencing studies in order to validate findings. This method will also be used on a larger set of tumour only samples in order to find precedence of these findings in a larger set of patient samples. Illumina HiSeq 2000; 46 bam
EGAD00001000403 The ENGAGE project is a FP7 funded EU project aiming to combine genetic and phenotype information from European population based cohorts. In this sub-project we aim to do whole exome sequencing of individuals selected from Health 2000 and FINRISK cohorts. Individuals have been selected based on their metabolic trait phenotypes Illumina HiSeq 2000; 394 bam
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
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
EGAD00001000243 Melanoma-TIL Study Exomes Illumina HiSeq 2000; 43 bam,cram
EGAD00001000350 We propose to definitively characterise the somatic genetics of a number of pediatric malignant tumours including ependymoma, high grade glioma and central nervous system primitive neurectodermal tumours through generation of comprehensive catalogues of somatic mutations by high coverage genome sequencing. Illumina HiSeq 2000; 17 bam
EGAD00001000199 ORCADES_WGA Illumina HiSeq 2000; 400 bam
EGAD00001000309 UK10K_OBESITY_GS REL-2012-11-27 Illumina HiSeq 2000; 424 vcf
EGAD00001000300 UK10K_OBESITY_GS_REL_2012_07_05 Illumina HiSeq 2000; 430 bam
EGAD00001000613 UK10K_NEURO_ASD_MGAS REL-2013-04-20 Illumina HiSeq 2000; 97 vcf
EGAD00001000604 n 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 and from studies in the mouse, it appears that an epigenetic memory of the starting cell type is carried over to hiPSCs. However a comprehensive comparative study of the characteristics of these hiPSCs has been missing from the literature. Importantly studies which aimed to address these aspects of hiPSCs have used cells from different patients. In order to avoid this important confounding variable and to keep the genetic background constant, tissue samples were procured from the patients and reprogrammed to iPS cells. The transcriptomes of these iPS cells will be compared. Protocol: primary cultures of cells were reprogrammed to iPS cells. RNA was extracted using a standard column extraction kit. Illumina HiSeq 2000; 47 bam
EGAD00001000204 Hearing loss in adults from South Carolina Illumina HiSeq 2000; 10 bam
EGAD00001000385 Wholegenome libraries will be prepared from at least two serial samples reflecting different stages of disease progression and matched constitutional DNA for 30 Myeloproliferative Disease samples. Five lanes of Illumina HiSeq sequencing will be performed on each of the tumour samples and four lanes for each of the constitutional DNA. Sequencing data will mapped to build 37 of the human reference genome and analysis will be performed to characterize the spectrum of somatic variation present in these samples including single base pair mutations, insertions, deletions as well as larger structural variants and genomic rearrangements. Illumina HiSeq 2000; 108 bam,cram
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
EGAD00001000252 Evaluation of PCR library method on whole genome samples Illumina HiSeq 2000; 12 bam
EGAD00001000253 AML targeted resequencing study Illumina HiSeq 2000; 1,972 bam
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
EGAD00001000387 This study aims to whole genome sequence DNA derived from breast cancer patients who received neo-adjuvany chemotherapy. All patients had multiple biopsies performed before chemotherapy. Patients who had residual disease after the course of treatment underwent a further biopsy. We aim to characterise the mutations involved. Illumina HiSeq 2000; 35 bam
EGAD00001000302 This experiment is looking at the mutational signatures generated by engineered HRAS mutations by using whole genome sequence generated on massively parallel next generation sequencers. Illumina HiSeq 2000; 6 bam
EGAD00001000200 Dilgom Exome Illumina HiSeq 2000; 130 bam
EGAD00001000251 De novo mutations in schizophrenia Illumina HiSeq 2000; 611 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
EGAD00001000245 Pulldown cytosine deaminases Illumina HiSeq 2000; 20 bam
EGAD00001000247 Integrative Oncogenomics of multiple myeloma Illumina HiSeq 2000; 51 bam
EGAD00001000264 Resistance towards chemotherapy is one of the main causes of treatment failure and death among breast cancer patients.The main objective of this project is to identify genetic mechanisms causing some breast cancer patients not to respond to a particluar type of chemotherapy (epirubicin) while other patients respond very well to the same treatment. In the project we will perform genome / exome sequencing of a selection of breast cancer patients (n=30). These patients are drawn from a cohort where all patients have recieved treatment with epirubicin monotherapy before surgical removal of a locally advanced breast tumour, and where all patients have been subjected to objective evaluation of the response to the therapy. Subsequent to sequencing, we will analyse the data and compare with the clinical data for each patient (object response to therapy). The main aim being to identify mutations that are associated with resistance to epirubicin. Identification of mutations with strong predictive value, may have a direct impact on cancer treatment since it opens the possibility for genetic testing of a tumour, and desicion on which drug is likely to work best, prior to treatment start. Illumina HiSeq 2000; 29 bam
EGAD00001000349 These samples are from locally advanced breast cancers that have been treated with epirubicin monotherapy before surgery. We will sequence some samples from patients with good response to the therapy and some with poor response to the therapy. Illumina HiSeq 2000; 33 bam
EGAD00001000360 The genome-wide landscape of somatically acquired mutations in mesothelioma has not been deeply characterised to date, but advances in DNA sequencing technology now allow this to be addressed comprehensively. Harnessing massively parallel DNA sequencing platforms, we will identify somatically acquired point mutations in all coding regions of the genome from patients with mesothelioma. In addition, using paired-end sequencing, we will map copy number changes and genomic rearrangements from the same patients. Illumina HiSeq 2000; 232 bam,cram
EGAD00001000265 This Study uses a focused bespoke bait pull down library method to target findings of Chondrosarcoma whole genome and whole exome sequencing studies in order to validate findings. This method will also be used on a larger set of tumour only samples in order to find precedence of these findings in a larger set of patient samples. Illumina HiSeq 2000; 190 bam
EGAD00001000304 ICGC prostate cancer miRNA sequencing Illumina HiSeq 2000; 8 fastq
EGAD00001000434 UK10K_NEURO_ASD_BIONED REL-2013-04-20 Illumina HiSeq 2000; 77 vcf
EGAD00001000418 UK10K_RARE_NEUROMUSCULAR REL-2013-04-20 Illumina HiSeq 2000; 140 vcf
EGAD00001000305 ICGC prostate cancer RNA sequencing Illumina HiSeq 2000; 12 fastq
EGAD00001000433 UK10K_NEURO_ABERDEEN REL-2013-04-20 Illumina HiSeq 2000; 392 vcf
EGAD00001000440 UK10K_NEURO_GURLING REL-2013-04-20 Illumina HiSeq 2000; 48 vcf
EGAD00001000432 UK10K_OBESITY_SCOOP REL-2013-04-20 Illumina HiSeq 2000; 985 vcf
EGAD00001000442 UK10K_NEURO_IOP_COLLIER REL-2013-04-20 Illumina HiSeq 2000; 172 vcf
EGAD00001000430 UK10K_NEURO_UKSCZ REL-2013-04-20 Illumina HiSeq 2000; 554 vcf
EGAD00001000438 UK10K_NEURO_EDINBURGH REL-2013-04-20 Illumina HiSeq 2000; 234 vcf
EGAD00001000439 UK10K_NEURO_FSZNK REL-2013-04-20 Illumina HiSeq 2000; 285 vcf
EGAD00001000437 UK10K_NEURO_ASD_TAMPERE REL-2013-04-20 Illumina HiSeq 2000; 55 vcf
EGAD00001000435 UK10K_NEURO_ASD_FI REL-2013-04-20 Illumina HiSeq 2000; 84 vcf
EGAD00001000431 UK10K_OBESITY_GS REL-2013-04-20 Illumina HiSeq 2000; 428 vcf
EGAD00001000338 We propose to definitively characterise the somatic genetics of ER+ve, HER2-ve breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses. Illumina HiSeq 2000; 3 bam
EGAD00001000441 UK10K_NEURO_IMGSAC REL-2013-04-20 Illumina HiSeq 2000; 113 vcf
EGAD00001000436 UK10K_NEURO_ASD_GALLAGHER REL-2013-04-20 Illumina HiSeq 2000; 77 vcf
EGAD00001000597 Illumina HiSeq 2000; 212 bam
EGAD00001000603 We recently used the Agilent SureSelect platform to re-sequence a set of genes known to be mutated in human AML. The results from 10 AML DNA samples were very satisfactory, but the effort required was significant. Thus, we decided to re-sequence the same genes using the Haloplax system for target enrichment in 48 AML samples. We planned to do this using MiSeq and have data from a pilot of 3 samples. The data is promising but coverage appears pathcy so far. However, in order to get a better understanding of the data we will need deeper sequencing. We will need two lanes of HiSeq to get the same degree coverage as Sureselect. his 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; 54 bam,cram
EGAD00001000614 UK10K_NEURO_ASD_SKUSE REL-2013-04-20 Illumina HiSeq 2000; 341 vcf
EGAD00001000615 UK10K_NEURO_FSZ REL-2013-04-20 Illumina HiSeq 2000; 128 vcf
EGAD00001000598 The Ethiopian area stands among the most ancient ones ever occupied by human populations and their ancestors. Particularly, according to archaeological evidences, it is possible to trace back the presence of Hominids up to at least 3 million years ago. Furthermore, the present day human populations show a great cultural, linguistic and historic diversity which makes them essential candidate to investigate a considerable part of the African variability. Following the typing of 300 Ethiopian samples on Illumina Omni 1M (see Human Variability in Ethiopia project, previously approved by the Genotyping committee) we now have a clearer idea on which populations living in the area include the most of the diversity. This project therefore aims to sequence the whole genome of 300 individuals at low (4-8x) depth belonging to the six most representative populations of the Ethiopian area to produce a unique catalogue of variants peculiar of the North East Africa. Furthermore 6 samples (one from each population) will also be sequenced at high (30x) depth to ensure full coverage of the diversity spectrum. The retrieved variants will be of great help in evaluating the demographic dynamics of those populations as well as shedding light on the migrations out of Africa. Illumina HiSeq 2000; 120 bam
EGAD00001000616 Pilocytic Astrocytoma ICGC PedBrain whole genome sequencing Illumina HiSeq 2000; 192 bam
EGAD00001000286 Whole-exome study of congenital macrothrombocytopenia Illumina HiSeq 2000; 21 fastq
EGAD00001000601 Illumina HiSeq 2000; 1 bam
EGAD00001000617 Pilocytic Astrocytoma ICGC PedBrain RNA sequencing Illumina HiSeq 2000; 73 fastq
EGAD00001000599 We have collected material from a patient who had BrafV600E mutant melanoma that was treated with PLX4032. We have germline DNA from the patient and DNA and RNA from distinct lesions before and after treatment with PLX4032. We have transcriptome sequenced these samples to obtain a snap shot of the mechanisms of resistance that are operative. Illumina HiSeq 2000; 6 bam
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
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
EGAD00001000596 This project is to develop and validate a method to detect de novo mutations in a foetal genome through deep sequencing of cell-free DNA from the plasma of pregnant women. 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; 5 bam
EGAD00001000421 The aim of this project is to identify rare variants in the 1q region associated with type 2 diabetes. To this end 651 case samples and 651 control samples from six populations have been pooled (pool sizes range from 27-33 individuals), and are being sequenced. The hybridization solution being used captures the exons and UTRs of genes in the 1q region. Illumina HiSeq 2000; 48 bam
EGAD00001000429 UK10K_OBESITY_TWINSUK REL-2013-04-20 Illumina HiSeq 2000; 68 vcf
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
EGAD00001000370 This dataset is compromised of 5 sequencing experiments from a single patient with sporadic and recurring parathyroid carcinoma. The samples include whole genome sequence of the primary tumor, the first recurrent tumor and peripheral blood. Whole transcriptome sequence of the first and second recurrent tumors are also included. Illumina HiSeq 2000; 5 bam
EGAD00001000427 Illumina HiSeq 2000; 30 bam
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
EGAD00001000634 The ETV6-RUNX1 fusion gene, found in 25% of childhood acute lymphoblastic leukemia (ALL), is acquired in utero but requires additional somatic mutations for overt leukemia. We used exome and low-coverage whole-genome sequencing to characterize the critical secondary events associated with leukemic transformation. RAG-mediated deletions emerge as the dominant mutational process, accounting for at least 43% of genomic rearrangements and characterized by the presence of recombination signal sequence motifs near the breakpoints; incorporation of non-templated sequence at the junction and a ten-fold enrichment at promoters and enhancers of genes actively transcribed in early B-lineage development. Single-cell tracking shows that this mechanism is not restricted to one founder cell but is rather active throughout leukemic evolution. Integration of point mutation and rearrangement data identifies recurrent inactivation of ATF7IP and MGA as two new tumor suppressor genes.Thus, a remarkably parsimonious mutational process transforms ETV6-RUNX1 lymphoblasts, striking promoters and enhancers of the genes that normally control B-cell differentiation. Illumina HiSeq 2000; 2 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
EGAD00001000324 We will sequence the RNA of lymphoblast samples, transformed with EBV, which have poikiloderma syndrome with mutations in c16orf57. The aim of the experiment is to characterise RNA structural effects in this disease. Illumina HiSeq 2000; 4 bam
EGAD00001000372 We conducted whole genome sequencing and DNA SNP array of 12 uveal melanoma genomes and their matched DNA from blood. We also conducted RNA-seq of the 12 tumour samples. Illumina HiSeq 2000; 24 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
EGAD00001000654 DATA FILES FOR BALL-PAX5 Illumina HiSeq 2000; 153 bam
EGAD00001000659 Illumina HiSeq 2000; 12 bam
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
EGAD00001000662 We propose to definitively characterise the somatic genetics of Triple negative breast cancer through generation of comprehensive catalogues of somatic mutations in 500 cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses. This study will use a bespoke bait set to pulldown regions of interest found in whole genome sequencing to validate mutations found. Illumina HiSeq 2000; 46 bam
EGAD00001000663 This study aims to re-sequence findings from whole genome studies using a bespoke pulldown method to validate mutations in those genomes sequenced. Illumina HiSeq 2000; 47 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
EGAD00001000671 Primary sclerosing chloangitis is a rare autoimmune disease of the liver (prevalence = 10/100,000) with a mean age of onset of 40 years. We are currently undertaking GWAS and immunochip experiments to identify loci underlying PSC susceptibility. Through our collaborators at the University of Calgary we have access to DNA from three parent-offspring trios where the children required liver transplants due to PSC before the age of 9. These are extremely rare cases indeed and we believe that exome-sequencing represents a powerful means of identifying the causal mutation underlying this severe phenotype. Illumina HiSeq 2000; 5 bam
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
EGAD00001000675 RNA-seq for monocytes and neutrophils Illumina HiSeq 2000; 12 fastq
EGAD00001000674 DNaseI-seq for monocytes Illumina HiSeq 2000; 4 fastq
EGAD00001000673 WGBS-seq for monocytes and neutrophils Illumina HiSeq 2000; 12 bam,readme_file
EGAD00001001326 Whole genome sequencing of single adult t-cell leukemia/lymphoma case Illumina HiSeq 2000; 2 bam
EGAD00001001333 Whole exome sequencing BAM files for samples from the BRIDGE Consortium with pathogenic or likely pathogenic variants on genes linked to bleeding or platelet disorders. Illumina HiSeq 2000; 28 bam
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
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
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
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
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
EGAD00001000640 Transcriptome studies in patients with rare genetic diseases can potentially aid in the interpretation of likely causal genetic variation through identification of altered transcript abundance and/or structure. RNA-Seq is the most sensitive assay for both investigating transcript structure and abundance The primary aim of this pilot project is to investigate to what degree integrating exome-Seq and RNA-Seq data on the same individual can accelerate the identification of causal alleles for rare genetic diseases. There are two main strands to this: (i) identifying which variants discovered in exome-seq appear to be having a functional impact on transcripts, and (ii) identifying transcript outliers, especially among known causal genes, that may not necessarily have a causal variant identified from exome sequencing. The latter may identify the presence of causal variants that lie far from coding regions (e.g. the formation of cryptic splice sites deep within introns, or loss of long range regulatory elements), which can be confirmed with further targeted genetic assays. Just over 50% of all disease-causing variants recorded in the Human Gene Mutation Database (HGMD) affect transcript structure and abundance (e.g. nonsense SNVs, essential splice site SNVs, frameshifting indels, CNVs). This pilot project will study RNA from lymphoblastoid cell-lines from 12 patients with primordial dwarfism syndromes, for 10 of these samples we have previously generate exome data as part of our collaboration with the group of Prof Andrew Jackson. The two remaining samples are positive controls where the causal mutation is known, and is known to affect transcript structure and/or abundance. Primordial dwarfism is a prime candidate for these RNA-seq studies because all known causal mutations to date have key roles in DNA replication and thus, unsurprisingly, the products of the causal genes are typically ubiquitously expressed. Each RNA will be sequenced, with two technical replicates (independent RT-PCR and libraries) per sample, and each replicate run in 1/2 of a HiSeq lane using 100bp paired reads. Samples preparation was as follows :The cells were grown to confluency, then pellets frozen at -80. RNA samples were prepared using the Qiagen RNeasy kit, then nanodropped and analyzed using the bioanalyzer to determine concentration and purity. 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; 24 bam
EGAD00001000899 We propose to definitively characterise the somatic genetics of Metastatic breast cancer through generation of comprehensive catalogues of somatic mutations in Metastatic breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses. Illumina HiSeq 2000; 41 bam,cram
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
EGAD00001001260 Illumina HiSeq 2000; 2 fastq
EGAD00001000694 This is an ongoing project and continuation to all the sequencing we have been doing over the last few years. We have some additional families and probands with syndromes of insulin resistance not previously sequenced within uk10k or other core funded projects. We would like to complete the sequencing in all of the good quality families and probands we have, this would require another ~50 samples to be WES sequenced. This cohort has already proven to be a rich source of interesting findings with papers in Science and Nature genetics. Illumina HiSeq 2000; 68 bam,cram
EGAD00001000695 DATA FILES FOR SJLGG Illumina HiSeq 2000; 46 bam
EGAD00001000696 The Ethiopian area stands among the most ancient ones ever occupied by human populations and their ancestors. Particularly, according to archaeological evidences, it is possible to trace back the presence of Hominids up to at least 3 million years ago. Furthermore, the present day human populations show a great cultural, linguistic and historic diversity which makes them essential candidate to investigate a considerable part of the African variability. Following the typing of 300 Ethiopian samples on Illumina Omni 1M (see Human Variability in Ethiopia project, previously approved by the Genotyping committee) we now have a clearer idea on which populations living in the area include the most of the diversity. This project therefore aims to sequence the whole genome of 300 individuals at low (4-8x) depth belonging to the six most representative populations of the Ethiopian area to produce a unique catalogue of variants peculiar of the North East Africa. Furthermore 6 samples (one from each population) will also be sequenced at high (30x) depth to ensure full coverage of the diversity spectrum. The retrieved variants will be of great help in evaluating the demographic dynamics of those populations as well as shedding light on the migrations out of Africa. Illumina HiSeq 2000; 5 bam
EGAD00001000291 Exome sequencing identifies mutation of the ribosome in T-cell acute lymphoblastic leukemia Illumina HiSeq 2000; 128 bam
EGAD00001000625 The main objective of this benchmark is the comparison of the full sequencing pipeline of different ICGC partners, including procedures, methods and performance of library preparation and whole-genome deep-sequencing. A secondary objective will be a follow-up comparison of data analysis pipelines for identification of germline and somatic variants subsequent to the results of the ICGC Somatic Variant Calling Pipeline Benchmark. Illumina HiSeq 2000; 2 bam
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
EGAD00001000652 Pulldown experiments will be performed on a number of patients with Myeloproliferative Neoplasms (MPN). The pulldown will be a bespoke design targeting known mutations, this pulldown will be sequenced and analysed to inform prevalence of mutations and to inform to the possibility of use as a diagnostic tool. Illumina HiSeq 2000; 1,036 bam
EGAD00001000292 Whole genome sequencing analysis was performed on 6 patients within matched germline, follicular lymphoma and transformed follicular lymphoma. Illumina HiSeq 2000; 20 bam
EGAD00001000667 Illumina HiSeq 2000; 72 bam
EGAD00001000711 Illumina HiSeq 2000; 42 bam
EGAD00001000713 Illumina HiSeq 2000; 12 bam
EGAD00001000712 Illumina HiSeq 2000; 72 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
EGAD00001000710 Whole Genome Bisulfite-seq of four B cell samples Illumina HiSeq 2000; 4 bam
EGAD00001000737 Whole exome sequencing data from 30 donors (46 tumors and 30 non-tumoral whole exome sequencing, paired-end, HiSeq 2000, Illumina) collected by the Inserm U674, PI Jessica Zucman-Rossi - Institut National du Cancer (INCa), PI Fabien Calvo, France. Illumina HiSeq 2000; 76 bam
EGAD00001001050 We propose to biopsy 20 consented BRAF mutant melanoma patients at Addenbrooke's Hospital pre-treatment with vemurafenib and also upon the development of resistant disease, with the aim of using exome sequence and SNP6 data to identify novel sequence variants and copy number alterations that can be used to validate observed resistance mechanisms in our cell line models and also to use these models to inform as to likely candidate small molecule inhibitors to overcome resistance and that could be tested in the clinical trial setting. Illumina HiSeq 2000; 8 cram
EGAD00001000856 Illumina HiSeq 2000; 1 fastq
EGAD00001000770 We aim to provide a powerful reference set for genome-wide association studies (GWAS) in African populations. Our pilot study to sequence 100 individuals each from Fula, Jola, Mandinka and Wollof from the Gambia to low coverage has been completed - this first part of the main effort will make available low coverage WGS data for 400 individuals from multiple ethnic groups in Burkina Faso, Cameroon, Ghana and Tanzania. 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; 32 cram
EGAD00001000771 We aim to provide a powerful reference set for genome-wide association studies (GWAS) in African populations. Our pilot study to sequence 100 individuals each from Fula, Jola, Mandinka and Wollof from the Gambia to low coverage has been completed - this first part of the main effort will make available low coverage WGS data for 400 individuals from multiple ethnic groups in Burkina Faso, Cameroon, Ghana and Tanzania. 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 bam,cram
EGAD00001000672 Whole-genome Bisulfite sequencing of two multiple myeloma samples and one pooled sample of plasma cells. Illumina HiSeq 2000; 3 bam
EGAD00001000721 This is a continuation of the Chordoma Sequencing Project. All cancers arise due to somatically acquired abnormalities in DNA sequence. Systematic sequencing of cancer genomes allows acquisition of complete catalogues of all classes of somatic mutation present in cancer. These mutation catalogues will allow identification of the somatically mutated cancer genes that are operative and characterise patterns of somatic mutation that may reflect previous exogenous and endogenous mutagenic exposures. In this application, we aim to perform whole genome sequencing on 10 chordoma matched genome pairs. RNA Sequencing/Methylation and SNP6 and an additional sequencing of three cancer cell lines will be added to this work. Illumina HiSeq 2000; 20 bam,cram
EGAD00001000397 The Cardiogenics re-sequencing study will consist of three parts: Eight pools of 25 individuals will be sequenced using a Nimblegen hybrid-capture solution specific to miRNA sequences, 80 pools of 25 individuals will be sequenced using a custom Agilent SureSelect array covering genes associated with coronary artery disease (CAD) and myocardial infarction (MI), 10 individuals from families with a history of CAD/MI will be exome sequenced using the Sanger exome array. The experiment will use the early onset patients from the German MI cohort and the UK BHF CAD/MI cohort both of which have strong family history. For controls we will consider individuals from the UKBS and KORA cohorts. Illumina HiSeq 2000; 47 bam
EGAD00001000689 Whole genome DNA sequencing was used to decrypt the phylogeny of multiple samples from distinct areas of cancer and morphologically normal tissue taken from the prostates of 3 men. We found that mutations were already present at high levels in morphologically normal tissue distant from the cancer suggesting clonal expansion. A subgroup of these mutations are present in adjacent cancer. A single nodule of cancer may contain multiple, predominantly genetically independent cancer clones each harbouring distinct ERG fusions. Separate lineages of cancer were in some cases connected by common low frequency mutations. Together our observations support the existence of a genetic field-effect underlying carcinogenesis The presence of a field effect, and of multiple cancer lineages within the same prostate pose serious questions regarding the effectiveness of focal therapy in those with a long life expectancy and imply that predicting future behaviour based on genetic analysis of single tumour sample may be unreliable. For each of three different prostates, multiple tumour samples (4, 5, and 3 depending on the case) and one normal tissue sample were whole genome sequenced with a matched blood sample using the Illumiuna HiSeq platform. Tumour samples were sequenced to a target depth of 50X and normals and blood to a target depth of 30X. Illumina HiSeq 2000; 18 bam
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
EGAD00001000722 Extension of angiosarcoma whole genome sequencing study Illumina HiSeq 2000; 8 cram
EGAD00001000624 Multifocality or multicentricity in breast cancer may be defined as the presence of two or more tumor foci within a single quadrant of the breast or within different quadrants of the same breast, respectively. This original classification of the breast cancer as multicentric or multifocal was based on the assumption that cancers arising in the same quadrant were more likely to arise from the same ductal structures than those occurring in separate areas of the breast. The problem with these definitions is that the ?quadrants? of the breast are arbitrary external designations, as no internal boundaries do exist. This project will therefore focus both on synchronous multifocal and multicentric tumors. The incidence of multifocal and multicentric breast cancers was reported to be between 13 and 75% depending on the definition used, the extent of the pathologic sampling of the breast and whether in situ disease is considered evidence of multicentricity (1). Although this incidence is variable, those figures show that it is a frequent phenomenon. Multiple (multifocal/multicentric) breast carcinomas, especially when occurring in the same breast, represent a real challenge for both pathologists and clinicians in terms of identifying the cellular origin and the best therapeutic management of the cancer. Multifocality or multicentricity has been associated with a number of more aggressive features including an increased rate of regional lymph node metastases and adverse patient outcome when compared with unifocal tumors (2-3), and a possible increased risk of local recurrence following breast conserving surgery (4). For the moment, the literature is divided on whether there is a corresponding impact on survival outcomes. Today, the current convention to stage and to treat multifocal and multicentric tumors is the classical tumor-node-metastasis (TNM) staging guidelines with which tumor size is assessed by the largest tumor focus without taking other foci of disease into consideration. If some papers, as the recent one from Lynch and colleagues, support the current staging convention (3), others, however, as Boyages et al. suggested that aggregate size and not the size of the largest lesion should be considered in order to refine the prognostic assessment of those tumors (5). On the top of that, the question whether multifocal/multicentric carcinomas are due to the spread of a single carcinoma throughout the breast or is due to multiple carcinomas arising simultaneously has been a matter of debate. Some studies suggested that multifocal breast cancer may result from either intramammary spread from a single primary tumor or multiple synchronous primary tumors; whereas others suggest that multiple breast carcinomas always arise from the same clone (6-8). Recently, Pietri and colleagues analyzed the biological characterization of a series of 113 multifocal/multicentric breast cancers (8) which were diagnosed over a 5-year period. The expression of estrogen (ER) and progesterone (PgR) receptors, Ki-67 proliferative index, expression of HER2 and tumor grading were prospectively determined in each tumor focus, and mismatches among foci were recorded. Mismatches in ER status were present in 5 (4.4%) cases and PgR in 18 (15.9%) cases. Mismatches in tumor grading were present in 21 cases (18.6%), proliferative index (Ki-67) in 17 (15%) cases and HER2 status in 11 (9.7%) cases. Interestingly, this heterogeneity among foci has led to 14 (12.4%) patients receiving different adjuvant treatments compared with what would have been indicated if we had only taken into account the biologic status of the primary tumor. This study therefore showed that differences in biological characteristics of multifocal/multicentric lesions play a crucial role in the adjuvant treatment decision making process. In this study, we will concentrate on a larger series of patients with multifocal invasive ductal breast cancer lesions. We aim at: 1. Evaluating the incidence of multifocality according to the different breast cancer molecular subtypes (ER-/HER2-, HER2+, ER+/HER2-). 2. Evaluating the incidence of multifocality in patients with hereditary breast cancer disease (presence of germline BRCA1 or BRCA2 mutations). Moreover, we would like to investigate if multifocal lesions with BRCA1 or BRCA2 mutations exhibit a characteristic combination of substitution mutation signatures and a distinctive profile of deletions as demonstrated recently by Nik-Zainal and colleagues (9). 3. Correlating multifocality with clinical information in order to define its influence on patients? survival (DFS and OS). 4. Carrying high coverage targeted gene sequencing of driver cancer genes and genes whose mutation is of therapeutic importance in order to compare clinically-relevant genetic differences between several multifocal breast cancer lesions. 5. Evaluating the impact of the distance between the different lesions on the clinical outcome but also on the genetic differences. 6. Comparing gene expression patterns between several multifocal breast cancer lesions and correlate them with the results of the targeted genes screen. 7. Characterizing the genomic and transcriptomic status of cancer related genes in metastatic lesions (local recurrence, positive lymph node or distant metastatic sites) from the same multifocal invasive ductal breast cancer patients in order to evaluate the consequence of genomic and transcriptomic heterogeneity of multifocal lesions on metastatic lesions. Multiple (multifocal/multicentric) breast carcinomas, especially when occurring in the same breast, represent a real challenge for both pathologists and clinicians in terms of identifying the cellular origin and the best therapeutic choice. This project has the potential to identify genetic/transcriptomic differences existing between several lesions constituting multifocal breast cancers, which in the routine clinical practice are usually considered to be homogeneous among them. We foresee validating significant results in a larger series of patients and this, in turn, could have a remarkable impact on the treatment and clinical management of multifocal breast cancers. Indeed, we hope to provide some evidence whether or not each focus matters in multifocal and multicentric breast cancer to define the adequate therapeutic approach, especially in the context of targeted therapies. The work to be done at Sanger will be target gene screen pooling of 1400 samples. Illumina HiSeq 2000; 908 bam,cram
EGAD00001000730 The VBSEQ project aims to combine available extensive genetic and phenotypic data to the latest high-throughput genome sequencing technology and ad hoc statistical analysis to identify new rare genetic variants underlying complex traits. Up to 100 Val Borbera samples will be sequenced to a 6x depth. Illumina HiSeq 2000; 110 bam
EGAD00001000729 The Val Borbera is a region characterized by low iodine and high prevalence of thyroid disorders, the commonest endocrine disorders in the general population. About 30% of the participants of the Val Borbera Project were affected by such disorders and were characterized by several parameters, TSH level, anti TPO antibodies, echography, family origin. Individuals with extreme phenotypes were identified and could be clustered based on family origin and genotype. We propose to exome sequence 6 of them, affected with true goiter, at high dept (40-60x) to obtain information on exonic rare variants. Due to the family structure and to the availability of whole genome sequence information on 110 individuals from the isolated population we expect to be able to identify putative causative variants for thyroid disorders that may be studied in the remaining affected individuals. Illumina HiSeq 2000; 8 bam
EGAD00001000728 Low coverage whole genome sequencing of samples from individuals from Friuli Venezia Giulia, an Italian genetic isolate population. Illumina HiSeq 2000; 199 bam
EGAD00001000731 This study includes Phase 2 whole-genome sequencing data (at 4x depth)of 100 individuals from an Italian genetic isolate population (Val Borbera, abbreviated VBI) of the Italian Network of Genetic Isolates (INGI). The INGI-VBI_SEQ2 project aims to combine available extensive genetic and phenotypic data to the latest high-throughput genome sequencing technology and ad hoc statistical analysis to identify new rare genetic variants underlying complex traits. Illumina HiSeq 2000; 100 bam
EGAD00001000732 RNA sequencing to validate findings of somatic pseudogenes acquired during cancer development Illumina HiSeq 2000; 3 cram
EGAD00001000400 The Cardiogenics re-sequencing study will consist of three parts: Eight pools of 25 individuals will be sequenced using a Nimblegen hybrid-capture solution specific to miRNA sequences, 80 pools of 25 individuals will be sequenced using a custom Agilent SureSelect array covering genes associated with coronary artery disease (CAD) and myocardial infarction (MI), 10 individuals from families with a history of CAD/MI will be exome sequenced using the Sanger exome array. The experiment will use the early onset patients from the German MI cohort and the UK BHF CAD/MI cohort both of which have strong family history. For controls we will consider individuals from the UKBS and KORA cohorts. Illumina HiSeq 2000; 12 bam
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
EGAD00001000401 Population based sequencing of whole genomes of Crohn's disease patients. Illumina HiSeq 2000; 2,926 bam
EGAD00001000402 The study will analyse by exome sequencing 42 Greek patients with premature MI and no vessel disease to identify genetic factors underlying this condition. Illumina HiSeq 2000; 46 bam
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
EGAD00001000405 In this project we will sequence the exomes of 250 patients with Parkinson's disease Illumina HiSeq 2000; 247 bam
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
EGAD00001000407 We are sequencing the exomes of patients with paroxysmal neurological disorders mainly focusing on migraine and epilepsy. Cases are collected from performance sites of members of the International Headache Genetics consortium and EuroEPINOMICS. Most cases have a strong family history. The study sample will include both cases and controls. Illumina HiSeq 2000; 327 bam
EGAD00001000408 We aim to whole-exome sequence DNA samples from 75 individuals with severe forms of Inflammatory Bowel Disease and related autoimmune diseases to identify the rare, highly penetrant, variants that we believe underlie these phenotypes. Case samples will be obtained from both new and existing (UK IBD Genetics Consortium) collaborators to ensure only the most extreme cases are sequenced. Illumina HiSeq 2000; 4 bam
EGAD00001000422 We perform whole exome sequencing on samples from a large IBD pedigree. The selected samples are from more distantly related family members (healthy and with IBD) and a set of matched population (Ashkenazy Jewish ancestry) samples. Illumina HiSeq 2000; 86 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
EGAD00001000410 We will perform exome sequencing on selected cases of splenic marginal zone lymphoma (SMZL) and diffuse large B-cell lymphoma (DLBCL) in order to characterise their genetic makeup and identify biomarkers for prognosis and prediction of treatment response. Illumina HiSeq 2000; 78 bam,cram
EGAD00001000411 These samples include exome sequences of family members with dyslipidemias from northern Finnish origin. Illumina HiSeq 2000; 68 bam
EGAD00001000412 We are sequencing the exomes of patients with paroxysmal neurological disorders mainly focusing on migraine and epilepsy. Cases are collected from performance sites of members of the International Headache Genetics consortium and EuroEPINOMICS. Most cases have a strong family history. The study sample will include both cases and controls. Illumina HiSeq 2000; 477 bam,cram
EGAD00001000740 UK10K_COHORT_ALSPAC REL-2012-06-02: Low-coverage whole genome sequencing; variant calling, genotype calling and phasing Illumina HiSeq 2000; 2,320 readme_file,tabix,vcf,vcf_aggregate
EGAD00001000738 Extension of angiosarcoma whole genome sequencing study Illumina HiSeq 2000; 4 cram
EGAD00001000739 We aim to provide a powerful reference set for genome-wide association studies (GWAS) in African populations. Our pilot study to sequence 100 individuals each from Fula, Jola, Mandinka and Wollof from the Gambia to low coverage has been completed - this first part of the main effort will make available low coverage WGS data for 400 individuals from multiple ethnic groups in Burkina Faso, Cameroon, Ghana and Tanzania. 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; 57 cram
EGAD00001000260 Hypodiploid acute lymphoblastic leukemia whole genome sequencing Illumina HiSeq 2000; 40 bam
EGAD00001000735 Here we present the genomes of three secondary angiosarcomas Illumina HiSeq 2000; 7 bam
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
EGAD00001000749 Illumina HiSeq 2000; 12 bam
EGAD00001000716 RNAseq data, Publication Fernandez-Cuesta et al., 2014, CD74-NRG1 fusions in lung adenocarcinoma Illumina HiSeq 2000; 25 fastq
EGAD00001000756 UK10K_OBESITY_SCOOP UK10K_EXOME_EXTRAS Illumina HiSeq 2000; 1 tabix,vcf
EGAD00001000760 dataset for esophageal cancer, 17pairs for whole-genome sequencing and 71pairs for whole-exome sequencing Illumina HiSeq 2000; 176 fastq
EGAD00001000704 Illumina HiSeq 2000; 44 bam
EGAD00001000753 UK10K_RARE_FINDWG REL-2013-09-09 Illumina HiSeq 2000; 4 tabix,vcf
EGAD00001000750 UK10K_RARE_FIND REL-2013-10-31 variant calling Illumina HiSeq 2000; 1,151 tabix,vcf
EGAD00001000755 UK10K_OBESITY_GS UK10K_EXOME_EXTRAS Illumina HiSeq 2000; 5 tabix,vcf
EGAD00001000757 UK10K_RARE_SIR UK10K_EXOME_EXTRAS Illumina HiSeq 2000; 2 tabix,vcf
EGAD00001000752 UK10K_RARE_CILWG REL-2013-09-09 Illumina HiSeq 2000; 4 tabix,vcf
EGAD00001000754 UK10K_RARE_NMWG REL-2013-09-09 Illumina HiSeq 2000; 5 tabix,vcf
EGAD00001000794 Small cell carcinoma of the ovary of hypercalcemic type (SCCOHT) is an extremely rare, aggressive cancer affecting children and young women. We identified germline and somatic inactivating mutations in the SWI/SNF chromatin-remodeling gene SMARCA4 in 75% (9/12) of SCCOHT patients in addition to SMARCA4 protein loss in 82% (14/17) of SCCOHT tumors, but in only 0.4% (2/485) of other primary ovarian tumors. These data implicate SMARCA4 in SCCOHT oncogenesis. Illumina HiSeq 2000; 11 bam
EGAD00001000706 Whole exome sequencing of 6 tumour and normal pairs of diffuse intrinsic pontine glioma (DIPG) Illumina HiSeq 2000; 12 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
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
EGAD00001000705 Whole genome sequencing of 20 tumour and normal pairs of diffuse intrinsic pontine glioma (DIPG) Illumina HiSeq 2000; 40 bam
EGAD00001000785 We propose to definitively characterise the somatic genetics of a selection of rare bone cancers through generation of comprehensive catalogues of somatic mutations by high coverage genome sequencing. Illumina HiSeq 2000; 33 bam,cram
EGAD00001000784 This study aims to target capture sequence regions of interest from DNA derived from breast cancer patients who received neo-adjuvant chemotherapy. All patients had multiple biopsies performed before chemotherapy. Patients who had residual disease after the course of treatment underwent a further biopsy. We aim to characterise the mutations involved. Illumina HiSeq 2000; 242 cram
EGAD00001000811 Whole exome sequencing of 6 HCCs and matched background liver in children with bile salt export pump deficiency. Illumina HiSeq 2000; 12 fastq
EGAD00001000797 This project aims to study at least 90 exomes from families with congenital heart disease. The samples have been selected at the Royal, Brompton Hospital in collaboration with Stuart Cook and Piers Daubeney. Ethic approval has been sought for in the UK and a HDMMC agreement for submitting these samples is in place at the WTSI. The phenotype we wil primarily focus our analysis is severe Left Ventricular Outflow Tract Obstructions (LVOTO) and Atrioventricular Septal Defect (AVSD). The indexed Agilent whole exome pulldown libraries will be sequenced on 75bp PE HiSeq (Illumina). Illumina HiSeq 2000; 48 bam
EGAD00001000796 This project aims to study at least 90 exomes from families with congenital heart disease. The samples have been selected in Leuven in collaboration with Koen Devriendt. Ethic approval has been sought for in Leuven, Belgium and a HDMMC agreement for submitting these samples is in place at the WTSI. The phenotype we wil primarily focus our analysis is severe Left Ventricular Outflow Tract Obstructions (LVOTO) and Atrioventricular Septal Defect (AVSD). The indexed Agilent whole exome pulldown libraries will be sequenced on 75bp PE HiSeq (Illumina). Illumina HiSeq 2000; 167 bam
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
EGAD00001000800 This project aims to study exomes from families and trios with congenital heart disease (CHD). The samples have been collected under the Competence Network - Congenital Heart Defects in Berlin, Germany. The phenotypes are mainly left ventricular outflow obstruction (aortic stenosis, bicuspd aortic valve disease coarctation and hypoplastic left heart), but will also include samples with hypoplastic right heart and atrioventricular septal defects. We will perform whole exome sequencing using Agilent sequence capture and Illumina HiSeq sequencing. Illumina HiSeq 2000; 406 bam,cram
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
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
EGAD00001000812 Sequencing of 350 cancer genes in BC samples from patients treated with either Epirubicin or Paclitaxel monotherapy in the neoadjuvant setting. Illumina HiSeq 2000; 364 cram
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
EGAD00001000724 Illumina HiSeq 2000; 68 bam
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
EGAD00001000795 Fernandez-Cuesta et al, 2014, Nature Communication, RNA Sequencing data set Illumina HiSeq 2000; 69 fastq
EGAD00001000782 Whole-genome sequencing was performed by Illumina Inc (San Diego, CA). Libraries were constructed with ~300bp insert length and paired-end 100bp reads were sequenced on Illumina HiSeq2000. Illumina HiSeq 2000; 199 bam
EGAD00001000821 Raw sequencing data for all samples in fastq format. Illumina HiSeq 2000; 767 fastq
EGAD00001000826 We propose to definitively characterise the somatic genetics of Osteosarcoma cancer through generation of comprehensive catalogues of somatic mutations by high coverage genome and transcriptome sequencing. Illumina HiSeq 2000; 10 cram
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
EGAD00001000776 UK10K_COHORT_IMPUTATION REL-2012-06-02: imputation reference panel (20140306); Merged UK10K+1000Genomes Phase 3 imputation reference panel added (20160420) Illumina HiSeq 2000; 3,781 other,readme_file
EGAD00001000746 Fernandez-Cuesta et al., RNAseq data Pipline Illumina HiSeq 2000; 25 fastq
EGAD00001000825 This study aims to define the landscape of somatic mutations in sun exposed human skin by deep sequencing, analyse their frequency and use the data to infer the effect of mutations on proliferating cell behaviour. The frequency of each mutation will reflect the size of the clone of cells in the tissue sample. By analyzing small samples, clones with as few as 100 cells will be detectable. Allele frequency distributions for each mutation will be used to infer cell fate using published methods (Klein et al. 2010). This study will shed unprecedented light on the early clonal events that lead to the emergence of cancer. Illumina HiSeq 2000; 454 cram
EGAD00001000824 RNA sequencing will be undertaken to reconstruct rearrangements at level of transcription to determine pathogenomic genomic events in chondromyxoid fibroma. Illumina HiSeq 2000; 1 cram
EGAD00001000847 Shwachman-Diamond syndrome (SDS) is a rare autosomal recessive disorder characterized by exocrine pancreatic insufficienc