recipe bioconductor-bayseq

Empirical Bayesian analysis of patterns of differential expression in count data

Homepage

https://bioconductor.org/packages/3.13/bioc/html/baySeq.html

License

GPL-3

Recipe

/bioconductor-bayseq/meta.yaml

Links

biotools: bayseq, doi: 10.1186/1471-2105-11-422

This package identifies differential expression in high-throughput 'count' data, such as that derived from next-generation sequencing machines, calculating estimated posterior likelihoods of differential expression (or more complex hypotheses) via empirical Bayesian methods.

package bioconductor-bayseq

Versions

2.26.0-0,  2.24.0-1,  2.24.0-0,  2.22.0-0,  2.20.0-0,  2.18.0-1,  2.16.0-0,  2.14.0-0,  2.12.0-0, 

2.26.0-0,  2.24.0-1,  2.24.0-0,  2.22.0-0,  2.20.0-0,  2.18.0-1,  2.16.0-0,  2.14.0-0,  2.12.0-0,  2.10.0-0

Depends

• bioconductor-edger >=3.34.0,<3.35.0

• bioconductor-genomicranges >=1.44.0,<1.45.0

• r-abind

• r-base >=4.1,<4.2.0a0

Required By

• bioconductor-segmentseq

• bioconductor-metaseqr2

• bioconductor-rcade

• bioconductor-clusterseq

• bioconductor-riboseqr

• bioconductor-tcc

• bioconductor-srnadiff

Installation

With an activated Bioconda channel (see 2. Set up channels), install with:

conda install bioconductor-bayseq

and update with:

conda update bioconductor-bayseq

or use the docker container:

docker pull quay.io/biocontainers/bioconductor-bayseq:<tag>

(see bioconductor-bayseq/tags for valid values for <tag>)

Link to this page

Render an badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-bayseq/README.html)