recipe bioconductor-bayseq

Empirical Bayesian analysis of patterns of differential expression in count data

Homepage:

https://bioconductor.org/packages/3.16/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:

2.31.0-1,  2.31.0-0,  2.28.0-0,  2.26.0-0,  2.24.0-1,  2.24.0-0,  2.22.0-0,  2.20.0-0,  2.18.0-1, 

2.31.0-1,  2.31.0-0,  2.28.0-0,  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 >=3.40.0,<3.41.0

• bioconductor-genomicranges >=1.50.0,<1.51.0

• r-abind

• r-base >=4.2,<4.3.0a0

Required By:

• bioconductor-srnadiff

• bioconductor-segmentseq

• bioconductor-rcade

• bioconductor-riboseqr

• bioconductor-tcc

• bioconductor-metaseqr2

• bioconductor-clusterseq

Installation

With an activated Bioconda channel (see 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>)

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