- recipe bioconductor-deepsnv
Detection of subclonal SNVs in deep sequencing data.
- Homepage:
https://bioconductor.org/packages/3.16/bioc/html/deepSNV.html
- License:
GPL-3
- Recipe:
- Links:
biotools: deepsnv
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.
- package bioconductor-deepsnv¶
-
- Versions:
1.44.0-0
,1.40.0-2
,1.40.0-1
,1.40.0-0
,1.38.0-0
,1.36.0-1
,1.36.0-0
,1.34.0-0
,1.32.0-0
,1.44.0-0
,1.40.0-2
,1.40.0-1
,1.40.0-0
,1.38.0-0
,1.36.0-1
,1.36.0-0
,1.34.0-0
,1.32.0-0
,1.30.0-1
,1.28.0-0
,1.26.1-0
,1.24.0-0
,1.22.0-0
,1.20.0-0
- Depends:
bioconductor-biostrings
>=2.66.0,<2.67.0
bioconductor-genomicranges
>=1.50.0,<1.51.0
bioconductor-iranges
>=2.32.0,<2.33.0
bioconductor-rhtslib
>=2.0.0,<2.1.0
bioconductor-summarizedexperiment
>=1.28.0,<1.29.0
bioconductor-variantannotation
>=1.44.0,<1.45.0
libblas
>=3.9.0,<4.0a0
libgcc-ng
>=12
liblapack
>=3.9.0,<4.0a0
libstdcxx-ng
>=12
r-base
>=4.2,<4.3.0a0
- Required By:
Installation
With an activated Bioconda channel (see set-up-channels), install with:
conda install bioconductor-deepsnv
and update with:
conda update bioconductor-deepsnv
or use the docker container:
docker pull quay.io/biocontainers/bioconductor-deepsnv:<tag>
(see bioconductor-deepsnv/tags for valid values for
<tag>
)
Download stats¶
Link to this page¶
Render an badge with the following MarkDown:
[](http://bioconda.github.io/recipes/bioconductor-deepsnv/README.html)