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Bioinformatics. 2011 Oct 1;27(19):2648-54. doi: 10.1093/bioinformatics/btr462. Epub 2011 Aug 9.

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

Author information

  • 1Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. fsathira@fas.harvard.edu

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.

PMID:
21828086
[PubMed - indexed for MEDLINE]
PMCID:
PMC3179661
Free PMC Article

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