Exome sequencing-based copy-number variation and loss of heterozygosity detection: ExomeCNV

J. Fah Sathirapongsasuti(University of California, Los Angeles), Hane Lee(University of California, Los Angeles), Basil A. Horst(University of California, Los Angeles), Georg Brunner(University of California, Los Angeles), Alistair J. Cochran(University of California, Los Angeles), Scott W. Binder(University of California, Los Angeles), John Quackenbush(University of California, Los Angeles), Stanley F. Nelson(University of California, Los Angeles)
Bioinformatics
August 9, 2011
10.1093/bioinformatics/btr462
Cited by 391Open Access
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Abstract

MOTIVATION: The ability to detect copy-number variation (CNV) and loss of heterozygosity (LOH) from exome sequencing data extends the utility of this powerful approach that has mainly been used for point or small insertion/deletion detection. RESULTS: We present ExomeCNV, a statistical method to detect CNV and LOH using depth-of-coverage and B-allele frequencies, from mapped short sequence reads, and we assess both the method's power and the effects of confounding variables. We apply our method to a cancer exome resequencing dataset. As expected, accuracy and resolution are dependent on depth-of-coverage and capture probe design. AVAILABILITY: CRAN package 'ExomeCNV'. CONTACT: fsathira@fas.harvard.edu; snelson@ucla.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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