A comparative analysis of algorithms for somatic SNV detection in cancer.

ABSTRACT:

Motivation

With the advent of relatively affordable high-throughput technologies, DNA sequencing of cancers is now common practice in cancer research projects and will be increasingly used in clinical practice to inform diagnosis and treatment. Somatic (cancer-only) single nucleotide variants (SNVs) are the simplest class of mutation, yet their identification in DNA sequencing data is confounded by germline polymorphisms, tumour heterogeneity and sequencing and analysis errors. Four recently published algorithms for the detection of somatic SNV sites in matched cancer-normal sequencing datasets are VarScan, SomaticSniper, JointSNVMix and Strelka. In this analysis, we apply these four SNV calling algorithms to cancer-normal Illumina exome sequencing of a chronic myeloid leukaemia (C

SUBMITTER: Roberts ND 

PROVIDER: S-EPMC3753564 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature