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News
May 1
Our paper Reliable detection of subclonal
single-nucleotide variants in tumor cell populations appeared in Nature Communications today (see also ETH Life). In this work, we present the deepSNV algorithm and demonstrate its capability to detect subclonal mutations present in only 1/10,000 cells.
Gerstung et al. (2012) Nat Commun 3:811. DOI: 10.1038/ncomms1814.
An R package for calling subclonal single-nucleotide variants from paired deep sequencing experiments.
1.2.3 Apr 2012
This package provides provides a quantitative variant caller for detecting subclonal mutations in ultra-deep (>=100x coverage) sequencing experiments. It assumes a comparative setup with a control experiment of the same loci and a beta-binomial model to discriminate sequencing errors and subclonal SNVs.
deepSNV is distributed under the GNU General Public License.
The source package has been tested on Mac and Linux, binary versions for Mac and Windows are also available.
The latest version is available on bioconductor package requires R >= 2.15 and bioconducor 2.10. This is the preferred way of installing deepSNV. You can install the package via
> source("http://bioconductor.org/biocLite.R")
> biocLite("deepSNV")
This site hosts an older version of deepSNV (0.99.3) that can be manually installed. It requires R >= 2.13 and the VGAM package that can be installed from CRAN with the
> install.packages("VGAM")
command, and Rsamtools which can be installed from Bioconductor via
> source("http://www.bioconductor.org/biocLite.R"); biocLite("Rsamtools")
You can install the actual package with
> install.packages("deepSNV", repos="http://www.cbg.ethz.ch/software/deepSNV")
And you are done.
After installation you can load the package with
> library(deepSNV)
and use the R help
> ?deepSNV
Additional examples can be found in the vignette:
> vignette("deepSNV")
When using deepSNV, please cite:
Gerstung, M., Beisel, C., Rechsteiner, M., Wild, P., Schraml, P., Moch, H., and Beerenwinkel, N. (2012). Reliable detection of subclonal single-nucleotide variants in tumor cell populations. Nat Commun, 3:811, doi: 10.1038/ncomms1814.
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