Package Recipe 'bioconductor-epigrahmm'

recipe bioconductor-epigrahmm

Epigenomic R-based analysis with hidden Markov models

Homepage:: https://bioconductor.org/packages/3.20/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:

1.18.0-2, 1.18.0-1, 1.18.0-0, 1.14.0-0, 1.10.0-0, 1.8.2-0, 1.6.4-1, 1.6.4-0, 1.6.0-1,

1.18.0-2, 1.18.0-1, 1.18.0-0, 1.14.0-0, 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:

on bioconductor-bamsignals >=1.42.0,<1.43.0
on bioconductor-bamsignals >=1.42.0,<1.43.0a0
on bioconductor-csaw >=1.44.0,<1.45.0
on bioconductor-csaw >=1.44.0,<1.45.0a0
on bioconductor-genomicranges >=1.62.0,<1.63.0
on bioconductor-genomicranges >=1.62.1,<1.63.0a0
on bioconductor-greylistchip >=1.42.0,<1.43.0
on bioconductor-greylistchip >=1.42.0,<1.43.0a0
on bioconductor-iranges >=2.44.0,<2.45.0
on bioconductor-iranges >=2.44.0,<2.45.0a0
on bioconductor-limma >=3.66.0,<3.67.0
on bioconductor-limma >=3.66.0,<3.67.0a0
on bioconductor-rhdf5 >=2.54.0,<2.55.0
on bioconductor-rhdf5 >=2.54.1,<2.55.0a0
on bioconductor-rhdf5lib >=1.32.0,<1.33.0
on bioconductor-rhdf5lib >=1.32.0,<1.33.0a0
on bioconductor-rsamtools >=2.26.0,<2.27.0
on bioconductor-rsamtools >=2.26.0,<2.27.0a0
on bioconductor-rtracklayer >=1.70.0,<1.71.0
on bioconductor-rtracklayer >=1.70.1,<1.71.0a0
on bioconductor-s4vectors >=0.48.0,<0.49.0
on bioconductor-s4vectors >=0.48.0,<0.49.0a0
on bioconductor-seqinfo >=1.0.0,<1.1.0
on bioconductor-seqinfo >=1.0.0,<1.1.0a0
on bioconductor-summarizedexperiment >=1.40.0,<1.41.0
on bioconductor-summarizedexperiment >=1.40.0,<1.41.0a0
on libblas >=3.9.0,<4.0a0
on libgcc >=14
on liblapack >=3.9.0,<4.0a0
on liblzma >=5.8.2,<6.0a0
on libstdcxx >=14
on libzlib >=1.3.1,<2.0a0
on r-base >=4.5,<4.6.0a0
on r-data.table
on r-ggplot2
on r-ggpubr
on r-magrittr
on r-mass
on r-matrix
on r-pheatmap
on r-rcpp
on r-rcpparmadillo
on r-scales

Additional platforms:

Installation¶

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi¶

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install bioconductor-epigrahmm

to add into an existing workspace instead, run:

pixi add bioconductor-epigrahmm

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda¶

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install bioconductor-epigrahmm

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-epigrahmm

with envname being the name of the desired environment.

Container¶

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

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

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

Integrated deployment¶

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

Download stats¶

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-epigrahmm/README.html)