Detection of subclonal SNVs in deep sequencing experiments.

Bioconductor version: Release (2.14)

This package provides provides a 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 new shearwater algorithm (beta) 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.

Author: Moritz Gerstung and Niko Beerenwinkel

Maintainer: Moritz Gerstung <moritz.gerstung at>

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PDF R Script An R package for detecting low frequency variants in deep sequencing experiments
PDF R Script Subclonal variant calling with multiple samples and prior knowledge using shearwater
PDF   Reference Manual
Text   NEWS


biocViews DataImport, GeneticVariability, Genetics, SNP, Sequencing, Software
Version 1.10.0
In Bioconductor since BioC 2.10 (R-2.15)
License GPL-3
Depends R (>= 2.13.0), Rsamtools(>= 1.4.3), GenomicRanges, IRanges, Biostrings, VGAM, methods, graphics, VariantAnnotation(>= 1.5.0), parallel
Imports Rsamtools
Suggests RColorBrewer, knitr
System Requirements
Depends On Me
Imports Me
Suggests Me GenomicFiles

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Package Source deepSNV_1.10.0.tar.gz
Windows Binary (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) deepSNV_1.10.0.tgz
Mac OS X 10.9 (Mavericks)
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