Publication

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

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

Abstract

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@genome.wustl.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Authors

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