- recipe bioconductor-epigrahmm
Epigenomic R-based analysis with hidden Markov models
- Homepage:
https://bioconductor.org/packages/3.18/bioc/html/epigraHMM.html
- License:
MIT + file LICENSE
- Recipe:
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:
1.10.0-0,1.8.2-0,1.6.4-1,1.6.4-0,1.6.0-1,1.6.0-0,1.2.2-1,1.2.2-0,1.2.0-0,1.10.0-0,1.8.2-0,1.6.4-1,1.6.4-0,1.6.0-1,1.6.0-0,1.2.2-1,1.2.2-0,1.2.0-0,1.0.1-0- depends bioconductor-bamsignals:
>=1.34.0,<1.35.0- depends bioconductor-bamsignals:
>=1.34.0,<1.35.0a0- depends bioconductor-csaw:
>=1.36.0,<1.37.0- depends bioconductor-csaw:
>=1.36.0,<1.37.0a0- depends bioconductor-genomeinfodb:
>=1.38.0,<1.39.0- depends bioconductor-genomeinfodb:
>=1.38.1,<1.39.0a0- depends bioconductor-genomicranges:
>=1.54.0,<1.55.0- depends bioconductor-genomicranges:
>=1.54.1,<1.55.0a0- depends bioconductor-greylistchip:
>=1.34.0,<1.35.0- depends bioconductor-greylistchip:
>=1.34.0,<1.35.0a0- depends bioconductor-iranges:
>=2.36.0,<2.37.0- depends bioconductor-iranges:
>=2.36.0,<2.37.0a0- depends bioconductor-limma:
>=3.58.0,<3.59.0- depends bioconductor-limma:
>=3.58.1,<3.59.0a0- depends bioconductor-rhdf5:
>=2.46.0,<2.47.0- depends bioconductor-rhdf5:
>=2.46.1,<2.47.0a0- depends bioconductor-rhdf5lib:
>=1.24.0,<1.25.0- depends bioconductor-rhdf5lib:
>=1.24.0,<1.25.0a0- depends bioconductor-rsamtools:
>=2.18.0,<2.19.0- depends bioconductor-rsamtools:
>=2.18.0,<2.19.0a0- depends bioconductor-rtracklayer:
>=1.62.0,<1.63.0- depends bioconductor-rtracklayer:
>=1.62.0,<1.63.0a0- depends bioconductor-s4vectors:
>=0.40.0,<0.41.0- depends bioconductor-s4vectors:
>=0.40.2,<0.41.0a0- depends bioconductor-summarizedexperiment:
>=1.32.0,<1.33.0- depends bioconductor-summarizedexperiment:
>=1.32.0,<1.33.0a0- depends libblas:
>=3.9.0,<4.0a0- depends libgcc-ng:
>=12- depends liblapack:
>=3.9.0,<4.0a0- depends libstdcxx-ng:
>=12- depends r-base:
>=4.3,<4.4.0a0- depends r-data.table:
- depends r-ggplot2:
- depends r-ggpubr:
- depends r-magrittr:
- depends r-mass:
- depends r-matrix:
- depends r-pheatmap:
- depends r-rcpp:
- depends r-rcpparmadillo:
- depends r-scales:
- requirements:
- additional platforms:
Installation
You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).
While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.
Given that you already have a conda environment in which you want to have this package, install with:
mamba install bioconductor-epigrahmm and update with:: mamba update bioconductor-epigrahmm
To create a new environment, run:
mamba create --name myenvname bioconductor-epigrahmm
with
myenvnamebeing a reasonable name for the environment (see e.g. the mamba docs for details and further options).Alternatively, 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¶
Render an 
badge with the following MarkDown:
[](http://bioconda.github.io/recipes/bioconductor-epigrahmm/README.html)
