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Copy number variation in inbred and wild mice

ABSTRACT: Copy number variants were determined in 3-5 males from 13 inbred laboratory mouse strains and 21 Mus musculus individuals caught in various geographic locations, using Nimblegen 385k arrays. CopyMap was used to predict CNVs.

ORGANISM(S): Mus musculus domesticus Mus musculus Mus spretus

PROVIDER: GSE24424 | GEO | 2010/12/31

SECONDARY ACCESSION(S): PRJNA133505

REPOSITORIES: GEO

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Copy number variation in inbred and wild mice

Project description:Copy number variants were determined in 3-5 males from 13 inbred laboratory mouse strains and 21 Mus musculus individuals caught in various geographic locations, using Nimblegen 385k arrays. CopyMap was used to predict CNVs. 3-5 males from 13 inbred strains and 21 Mus musculus caught in various geographic locations were compared to a single C57BL/6J individual by array comparative genome hybridisation.

2010-12-31 | E-GEOD-24424 | biostudies-arrayexpress

wuHMM: a robust algorithm to detect DNA copy number variation using long oligonucleotide microarray data

Project description:Copy number variants (CNVs) are currently defined as genomic sequences that are polymorphic in copy number and range in length from 1,000 to several million base pairs. Among current array-based CNV detection platforms, long-oligonucleotide arrays promise the highest resolution. However, the performance of currently available analytical tools suffers when applied to these data because of the lower signal:noise ratio inherent in oligonucleotide-based hybridization assays. We have developed wuHMM, an algorithm for mapping CNVs from array comparative genomic hybridization (aCGH) platforms comprised of 385,000 to more than 3 million probes. wuHMM is unique in that it can utilize sequence divergence information to reduce the false positive rate (FPR). We apply wuHMM to 385K-aCGH, 2.1M-aCGH, and 3.1M-aCGH experiments comparing the 129X1/SvJ and C57BL/6J inbred mouse genomes. We assess wuHMM’s performance on the 385K platform by comparison to the higher resolution platforms and we independently validate 10 CNVs. The method requires no training data and is robust with respect to changes in algorithm parameters. At a FPR of less than 10%, the algorithm can detect CNVs with five probes on the 385K platform and three on the 2.1M and 3.1M platforms, resulting in effective resolutions of 24 kb, 2-5 kb, and 1 kb, respectively. Keywords: CNV detection algorithm development and assessment All four samples in this series are hybridizations of genomic DNA from inbred mouse strains 129X1/SvJ versus C57BL6/J. The experiments were performed at increasing resolutions (one 385K, two 2.1M, and one 3.1M).

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Project description:Mus musculus strain:C57BL/6J | breed:inbred Raw sequence reads

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