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], Raul Alcantara [ctb], David Jones [ctb], Inigo Martincorena [ctb], Moritz Gerstung [aut, cre]
Bioconductor views DataImport GeneticVariability Genetics SNP Sequencing
MaintainerMoritz Gerstung <moritz.gerstung@ebi.ac.uk>
LicenseGPL-3
Version1.36.0
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("deepSNV")

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deepSNV documentation built on Nov. 8, 2020, 8:01 p.m.