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Detection of subclonal SNVs in deep sequencing data.

Bioconductor version: Release (3.19)

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>

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


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


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

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


biocViews DataImport, GeneticVariability, Genetics, SNP, Sequencing, Software
Version 1.50.0
In Bioconductor since BioC 2.10 (R-2.15) (12.5 years)
License GPL-3
Depends R (>= 2.13.0), methods, graphics, parallel, IRanges, GenomicRanges, SummarizedExperiment, Biostrings, VGAM, VariantAnnotation(>= 1.27.6)
Imports Rhtslib
System Requirements GNU make
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Suggests RColorBrewer, knitr, rmarkdown
Linking To Rhtslib(>= 1.13.1)
Depends On Me
Imports Me mitoClone2
Suggests Me GenomicFiles
Links To Me
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Source Package deepSNV_1.50.0.tar.gz
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macOS Binary (x86_64) deepSNV_1.50.0.tgz
macOS Binary (arm64) deepSNV_1.50.0.tgz
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