Bioinformatics Advance Access published online on June 19, 2009
Bioinformatics, doi:10.1093/bioinformatics/btp373
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VarScan: Variant detection in massively parallel sequencing of individual and pooled samples
The Genome Center at Washington University School of Medicine, St. Louis, Missouri 63108, USA.
*To whom correspondence should be addressed. Mr. Daniel Koboldt E-mail: dkoboldt{at}genome.wustl.edu
| Abstract |
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Summary: Massively parallel sequencing technologies hold incredible promise for the study of DNA sequence variation, particularly the identification of variants affecting human disease. The unprece-dented 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 chal-lenging, 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 align-ers. 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: Prof. Dmitrij Frishman
Received on April 16, 2009; revised on June 11, 2009; accepted on June 12, 2009