To install this package, start R and enter:

source("http://bioconductor.org/biocLite.R")
biocLite("deepSNV")

In most cases, you don't need to download the package archive at all.

deepSNV

Detection of subclonal SNVs in deep sequencing experiments.

Bioconductor version: 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 sanger.ac.uk>

Citation (from within R, enter citation("deepSNV")):

Installation

To install this package, start R and enter:

source("http://bioconductor.org/biocLite.R")
biocLite("deepSNV")

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("deepSNV")

 

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

Details

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
URL http://www.cbg.ethz.ch/software/deepSNV
Depends On Me
Imports Me
Suggests Me GenomicFiles

Package Archives

Follow Installation instructions to use this package in your R session.

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