Comment[ArrayExpressAccession] E-GEOD-29456 Public Release Date 2011-07-12 Investigation Title Effect of Advanced Paternal Age on Copy Number Variation in Offspring Comment[Submitted Name] Effect of Advanced Paternal Age on Copy Number Variation in Offspring Experiment Description This SuperSeries is composed of the following subset Series: GSE29454: Effect of Advanced Paternal Age on Copy Number Variation in Offspring (custom array) GSE29455: Effect of Advanced Paternal Age on Copy Number Variation in Offspring (commercial array) Refer to individual Series Date of Experiment Term Source Name EFO Term Source Version Term Source File http://www.ebi.ac.uk/efo/efo.owl Person Last Name Flatscher-Bader Person First Name Traute Person Mid Initials Person Email t.flatscher-bader@uq.edu.au Person Affiliation The University of Queensland Person Phone Person Fax Person Address The Queensland Brain Institute, The University of Queensland, The University of Queensland, Upland Road, QBI Building (79), Brisbane, Queensland, Australia Person Roles submitter Person Roles Term Source REF Person Roles Term Accession Number Normalization Type Normalization Term Accession Number Normalization Term Source REF Replicate Type Replicate Term Accession Number Replicate Term Source REF Experimental Design Experimental Design Term Accession Number Experimental Design Term Source REF Quality Control Type Quality Control Term Accession Number Quality Control Term Source REF Protocol Name P-GSE29456-1 P-GSE29456-6 P-GSE29456-3 P-GSE29456-9 P-GSE29456-8 P-GSE29456-10 P-GSE29456-7 P-GSE29456-2 P-GSE29456-4 P-GSE29456-5 Protocol Description ID_REF =
VALUE = Normalized log2 ratio (Cy5/Cy3) representing test/reference Labelled samples were hybridized to arrays, and arrays were washed following the protocol recommended by Agilent and using the manufacturer's commercial kits and equipment. 2 old (12-16 months of age) sires and 2 control (3 months of age) sires were mated to dams (3 months of age) to create 6 offspring of advanced paternal age (A) and 6 control offspring (C), respectively, with an even number of sexes within each group of offspring. Array scans were converted to intensity data with the Agilent Feature Extraction Software v10.7, applying the default setting for aCGH arrays and analyzed further with the Agilent DNA Analytics v4.0.76 software. Normalization of data was performed using the default settings on the Feature Extraction software. On the DNA Analytics software 'centralization' and the 'fuzzy zero global error model' algorithms were applied to the resulting data sets to take into account global and local noise. The ADM-2 algorithm inherent to the DNA Analytics software was utilized for the detection of genomic aberrations based on the relative signal intensity ratio, which reflects the relative copy number (rCN) between the test sample and the respective male or female reference sample. All aberrations supported in at least one sample by at least five probes, an average log(2) ratio (LR) signal of at least 0.3 or less than -0.3 and not present on self-hybridization arrays were selected. To obtain an estimate of CNV size and to differentiate between nested and unnested CNVs, immediately adjacent aberrations on the chromosome with a median change in LR signal in the same direction and less than 0.5 different from each other were joined. Some CNVs, particularly at sites of segmental duplications, may have a complex, repetitive sub-structure resulting in uneven signals detected on aCGH array. This together with noise generated from individual, suboptimal probes, may contribute to type 1 error. Therefore, from the selected aberrations, we selected for further inspection those that were either (a) present in more than 75% of the animals, or (b) were present on both arrays, or (c) contained a minimum number of ‘high confidence’ probes with a minimum height in LR. In regards to the latter, CNVs supported by no more than 10 probes contained more than 4 probes with an LR signal height of 0.5, which was also at least 0.4 above the respective self-hybridization signal. Aberrations supported by more probes were further considered if they contained at least 3 probes complying with these criteria for signal height. The Sample data table includes the data derived after analysis via the Agilent software and prior to post-filtering steps. The "post-filtering.txt" file, which is linked to the Series record as a supplementary file, includes all results that passed the analysis, i.e., for each CNV that passed the filtering criteria, all values are given for each probe contained within the CNV. These filtering steps included an analysis via the Agilent analysis software followed by further filtering to exclude false positives. All arrays were scanned on an Agilent Sure Scan Microarray High Resolution Scanner at 5μm double pass resolution. None. Tail tip DNA was extracted from all animals using standard phenol/chloroform extraction. DNA was washed twice with 70% ethanol, precipitated with 3M sodium acetate, resuspended in 10mM Tris and stored at 4C until use. Samples were processed following the protocol recommended by Agilent and using the manufacturer's commercial labelling kit. Protocol Software Protocol Hardware Protocol Contact Protocol Type bioassay_data_transformation hybridization grow feature_extraction feature_extraction feature_extraction image_aquisition specified_biomaterial_action nucleic_acid_extraction labeling Protocol Term Source REF Protocol Term Accession Number Experimental Factor Name SAMPLE TYPE FAMILY MEMBER SEX AGE TEST GROUP Experimental Factor Type sample type family member Sex age test group Experimental Factor Term Source REF Experimental Factor Term Accession Number Publication Title Publication Author List PubMed ID Publication DOI Publication Status Publication Status Term Source REF Publication Status Term Accession Number Comment[SecondaryAccession] GSE29456 Comment[GEOLastUpdateDate] 2011-07-11 Comment[AEExperimentType] comparative genomic hybridization by array Comment[GEOReleaseDate] 2011-07-11 Comment[ArrayExpressSubmissionDate] 2011-05-22 SDRF File E-GEOD-29456.sdrf.txt