Detecting somatic point mutations in cancer genome sequencing data: a comparison of mutation callers.

ABSTRACT:

Background

Driven by high throughput next generation sequencing technologies and the pressing need to decipher cancer genomes, computational approaches for detecting somatic single nucleotide variants (sSNVs) have undergone dramatic improvements during the past 2 years. The recently developed tools typically compare a tumor sample directly with a matched normal sample at each variant locus in order to increase the accuracy of sSNV calling. These programs also address the detection of sSNVs at low allele frequencies, allowing for the study of tumor heterogeneity, cancer subclones, and mutation evolution in cancer development.

Methods

We used whole genome sequencing (Illumina Genome Analyzer IIx platform) of a melanoma sample and matched blood, whole exome sequencing (Illumina

SUBMITTER: Wang Q 

PROVIDER: S-EPMC3971343 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature