Format

Send to

Choose Destination
Bioinformatics. 2009 Sep 1;25(17):2283-5. doi: 10.1093/bioinformatics/btp373. Epub 2009 Jun 19.

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

Author information

1
The Genome Center at Washington University School of Medicine, St Louis, MO 63108, USA. dkoboldt@genome.wustl.edu

Abstract

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
PMCID:
PMC2734323
DOI:
10.1093/bioinformatics/btp373
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Silverchair Information Systems Icon for PubMed Central
Loading ...
Support Center