deepSNV: Detection of subclonal SNVs in deep sequencing data.

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 <[email protected]>
Package repositoryView on Bioconductor
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deepSNV documentation built on Oct. 31, 2019, 9:05 a.m.