recipe bioconductor-epigrahmm

Epigenomic R-based analysis with hidden Markov models

Homepage:

https://bioconductor.org/packages/3.14/bioc/html/epigraHMM.html

License:

MIT + file LICENSE

Recipe:

/bioconductor-epigrahmm/meta.yaml

epigraHMM provides a set of tools for the analysis of epigenomic data based on hidden Markov Models. It contains two separate peak callers, one for consensus peaks from biological or technical replicates, and one for differential peaks from multi-replicate multi-condition experiments. In differential peak calling, epigraHMM provides window-specific posterior probabilities associated with every possible combinatorial pattern of read enrichment across conditions.

package bioconductor-epigrahmm

Versions:

1.2.2-0,  1.2.0-0,  1.0.1-0

Depends:

• bioconductor-bamsignals >=1.26.0,<1.27.0

• bioconductor-csaw >=1.28.0,<1.29.0

• bioconductor-genomeinfodb >=1.30.0,<1.31.0

• bioconductor-genomicranges >=1.46.0,<1.47.0

• bioconductor-greylistchip >=1.26.0,<1.27.0

• bioconductor-iranges >=2.28.0,<2.29.0

• bioconductor-limma >=3.50.0,<3.51.0

• bioconductor-rhdf5 >=2.38.0,<2.39.0

• bioconductor-rhdf5lib >=1.16.0,<1.17.0

• bioconductor-rsamtools >=2.10.0,<2.11.0

• bioconductor-rtracklayer >=1.54.0,<1.55.0

• bioconductor-s4vectors >=0.32.0,<0.33.0

• bioconductor-summarizedexperiment >=1.24.0,<1.25.0

• libblas >=3.8.0,<4.0a0

• libgcc-ng >=10.3.0

• liblapack >=3.8.0,<4.0a0

• libstdcxx-ng >=10.3.0

• r-base >=4.1,<4.2.0a0

• r-data.table

• r-ggplot2

• r-ggpubr

• r-magrittr

• r-mass

• r-matrix

• r-pheatmap

• r-rcpp

• r-rcpparmadillo

• r-scales

Required By:

Installation

With an activated Bioconda channel (see set-up-channels), install with:

conda install bioconductor-epigrahmm

and update with:

conda update bioconductor-epigrahmm

or use the docker container:

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

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

Download stats

Link to this page

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