This is the development version of deepSNV; for the stable release version, see deepSNV.
Detection of subclonal SNVs in deep sequencing data.Bioconductor version: Development (3.22)
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.
Author: Niko Beerenwinkel [ths], Raul Alcantara [ctb], David Jones [ctb], John Marshall [ctb], Inigo Martincorena [ctb], Moritz Gerstung [aut, cre]
Maintainer: Moritz Gerstung <moritz.gerstung at ebi.ac.uk>
Citation (from within R, entercitation("deepSNV")): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("deepSNV")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("deepSNV")Follow Installation instructions to use this package in your R session.
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