Title
VarScan: variant detection in massively parallel sequencing of individual and pooled samples
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 lenghts 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.
Year
DOI
Venue
2009
10.1093/bioinformatics/btp373
BIOINFORMATICS
Field
DocType
Volume
Genome,Massive parallel sequencing,Microsoft Windows,Computer science,Source code,Unix,Illumina dye sequencing,Pyrosequencing,Bioinformatics,Perl
Journal
25
Issue
ISSN
Citations 
17
1367-4803
48
PageRank 
References 
Authors
5.00
0
9
Name
Order
Citations
PageRank
Daniel C. Koboldt112512.00
Ken Chen220921.57
Todd Wylie3525.87
David E. Larson411011.19
Michael D. Mclellan5667.87
Elaine R. Mardis623923.34
George M. Weinstock7596.51
Richard K. Wilson822818.84
Li Ding916025.53