deepSNV: Detection of subclonal SNVs in deep sequencing data.
Version 1.22.0

This package provides provides quantitative variant callers for detecting subclonal mutations in ultra-deep (>=100x coverage) sequencing experiments. The deepSNV algorithm is used for a comparative setup with a control experiment of the same loci and uses a beta-binomial model and a likelihood ratio test to discriminate sequencing errors and subclonal SNVs. The shearwater algorithm computes a Bayes classifier based on a beta-binomial model for variant calling with multiple samples for precisely estimating model parameters such as local error rates and dispersion and prior knowledge, e.g. from variation data bases such as COSMIC.

Package details

AuthorNiko Beerenwinkel [ths], David Jones [ctb], Inigo Martincorena [ctb], Moritz Gerstung [aut, cre]
Bioconductor views DataImport GeneticVariability Genetics SNP Sequencing
MaintainerMoritz Gerstung <>
Package repositoryView on Bioconductor
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deepSNV documentation built on May 31, 2017, 11:17 a.m.