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Bioinformatics Advance Access originally published online on June 19, 2009
Bioinformatics 2009 25(17):2283-2285; doi:10.1093/bioinformatics/btp373
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© The Author 2009. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

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

Daniel C. Koboldt *, Ken Chen , Todd Wylie , David E. Larson , Michael D. McLellan , Elaine R. Mardis , George M. Weinstock , Richard K. Wilson and Li Ding

The Genome Center at Washington University School of Medicine, St Louis, MO 63108, USA

* To whom correspondence should be addressed.


  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.

Availability and Implementation: Source code and documentation freely available at http://genome.wustl.edu/tools/cancer-genomics implemented as a Perl package and supported on Linux/UNIX, MS Windows and Mac OSX.

Contact: dkoboldt{at}genome.wustl.edu

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: Dmitrij Frishman

Received on April 16, 2009; revised on June 11, 2009; accepted on June 12, 2009

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