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Feature-based classifiers for somatic mutation detection in tumour-normal paired sequencing data.

Bioinformatics (Oxford, England) | 2012

The study of cancer genomes now routinely involves using next-generation sequencing technology (NGS) to profile tumours for single nucleotide variant (SNV) somatic mutations. However, surprisingly few published bioinformatics methods exist for the specific purpose of identifying somatic mutations from NGS data and existing tools are often inaccurate, yielding intolerably high false prediction rates. As such, the computational problem of accurately inferring somatic mutations from paired tumour/normal NGS data remains an unsolved challenge.

Pubmed ID: 22084253 RIS Download

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Associated grants

  • Agency: Canadian Institutes of Health Research, Canada
    Id: 202452

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SAMtools/BCFtools (tool)

RRID:SCR_005227

Provide various utilities for manipulating alignments in the SAM format, including sorting, merging, indexing and generating alignments in a per-position format.

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