Title
Shimmer: detection of genetic alterations in tumors using next-generation sequence data.
Abstract
Motivation: Extensive DNA sequencing of tumor and matched normal samples using exome and whole-genome sequencing technologies has enabled the discovery of recurrent genetic alterations in cancer cells, but variability in stromal contamination and subclonal heterogeneity still present a severe challenge to available detection algorithms. Results: Here, we describe publicly available software, Shimmer, which accurately detects somatic single-nucleotide variants using statistical hypothesis testing with multiple testing correction. This program produces somatic single-nucleotide variant predictions with significantly higher sensitivity and accuracy than other available software when run on highly contaminated or heterogeneous samples, and it gives comparable sensitivity and accuracy when run on samples of high purity.
Year
DOI
Venue
2013
10.1093/bioinformatics/btt183
BIOINFORMATICS
Field
DocType
Volume
Computer science,Exome,Genetic variation,Multiple comparisons problem,Software,DNA sequencing,Data sequences,Bioinformatics,Statistical hypothesis testing
Journal
29
Issue
ISSN
Citations 
12
1367-4803
5
PageRank 
References 
Authors
0.55
9
5
Name
Order
Citations
PageRank
Nancy F. Hansen150.55
Jared J. Gartner250.55
Lan Mei350.55
Yardena Samuels450.89
James C. Mullikin5687.57