Display Settings:

Format

Send to:

Choose Destination
See comment in PubMed Commons below
Bioinformatics. 2012 Jul 15;28(14):1811-7. doi: 10.1093/bioinformatics/bts271. Epub 2012 May 10.

Strelka: accurate somatic small-variant calling from sequenced tumor-normal sample pairs.

Author information

  • 1Illumina, Inc., 5200 Illumina Way, San Diego, CA 92122, USA. csaunders@illumina.com

Abstract

MOTIVATION:

Whole genome and exome sequencing of matched tumor-normal sample pairs is becoming routine in cancer research. The consequent increased demand for somatic variant analysis of paired samples requires methods specialized to model this problem so as to sensitively call variants at any practical level of tumor impurity.

RESULTS:

We describe Strelka, a method for somatic SNV and small indel detection from sequencing data of matched tumor-normal samples. The method uses a novel Bayesian approach which represents continuous allele frequencies for both tumor and normal samples, while leveraging the expected genotype structure of the normal. This is achieved by representing the normal sample as a mixture of germline variation with noise, and representing the tumor sample as a mixture of the normal sample with somatic variation. A natural consequence of the model structure is that sensitivity can be maintained at high tumor impurity without requiring purity estimates. We demonstrate that the method has superior accuracy and sensitivity on impure samples compared with approaches based on either diploid genotype likelihoods or general allele-frequency tests.

AVAILABILITY:

The Strelka workflow source code is available at ftp://strelka@ftp.illumina.com/.

CONTACT:

csaunders@illumina.com

PMID:
22581179
[PubMed - indexed for MEDLINE]
Free full text
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Icon for HighWire
    Loading ...
    Write to the Help Desk