Bioinformatics. 2009 Sep 1;25(17):2283-5. Epub 2009 Jun 19.

VarScan: variant detection in massively parallel sequencing of individual and pooled samples.

Koboldt DC, Chen K, Wylie T, Larson DE, McLellan MD, Mardis ER, Weinstock GM, Wilson RK, Ding L.

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The Genome Center at Washington University School of Medicine, St Louis, MO 63108, USA. dkoboldt@genome.wustl.edu

Abstract

SUMMARY: Massively parallel sequencing technologies hold incredible promise for the study of DNA sequence variation, particularly the identification of variants affecting human disease. The unprecedented throughput and relatively short read lengths of Roche/454, Illumina/Solexa, and other platforms have spurred development of a new generation of sequence alignment algorithms. Yet detection of sequence variants based on short read alignments remains challenging, and most currently available tools are limited to a single platform or aligner type. We present VarScan, an open source tool for variant detection that is compatible with several short read aligners. We demonstrate VarScan's ability to detect SNPs and indels with high sensitivity and specificity, in both Roche/454 sequencing of individuals and deep Illumina/Solexa sequencing of pooled samples.

PMID:: 19542151; [PubMed - indexed for MEDLINE]
PMCID: PMC2734323

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Research Support, N.I.H., Extramural

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HG003079/HG/NHGRI NIH HHS/United States

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