Method to Detect CNV via Mated Short Reads
Medvedev, Fiume et al., Genome Research
Researchers at the University of Toronto describe a method to detect copy-number variation via mated short reads, wherein "matepairs mapping discordantly to the reference serve to indicate the presence of variation." CNVer — the team's algorithm — combines this information and allows researchers to "mitigate the sequencing biases that cause uneven local coverage and accurately predict CNVs." The team used CNVer on a recently described genome of a Yoruban individual and detected 4,879 CNVs. "CNVer can reconstruct the absolute copy counts of segments of the donor genome and evaluate the feasibility of using CNVer with low coverage datasets," the authors add.
NCI-Led Team Explores Predictive Use of Breast Cancer Risk Variants
March 18, 2010
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A NEJM study suggests 10 breast cancer risk variants add little information to non-genetic risk prediction models.
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