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

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ID: 294904
2009
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Abstract
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@genome.wustl.edu Supplementary information: Supplementary data are available at Bioinformatics online.
Reference Key
openalex_W2161815151 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Daniel C. Koboldt, Ken Chen, Todd Wylie, David E. Larson, Michael D. McLellan, Elaine R. Mardis, George M. Weinstock, Richard K. Wilson, Li Ding
Journal BMC Bioinformatics
Year 2009
DOI
10.1093/bioinformatics/btp373
URL
https://academic.oup.com/bioinformatics/article-pdf/25/17/2283/48993337/bioinformatics_25_17_2283.pdf
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