- recipe bioconductor-segmenter
Perform Chromatin Segmentation Analysis in R by Calling ChromHMM
Chromatin segmentation analysis transforms ChIP-seq data into signals over the genome. The latter represents the observed states in a multivariate Markov model to predict the chromatin's underlying states. ChromHMM, written in Java, integrates histone modification datasets to learn the chromatin states de-novo. The goal of this package is to call chromHMM from within R, capture the output files in an S4 object and interface to other relevant Bioconductor analysis tools. In addition, segmenter provides functions to test, select and visualize the output of the segmentation.
- package bioconductor-segmenter¶
- depends bioconductor-bamsignals:
- depends bioconductor-chipseeker:
- depends bioconductor-chromhmmdata:
- depends bioconductor-complexheatmap:
- depends bioconductor-genomicranges:
- depends bioconductor-iranges:
- depends bioconductor-s4vectors:
- depends bioconductor-summarizedexperiment:
- depends r-base:
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-segmenter and update with:: mamba update bioconductor-segmenter
To create a new environment, run:
mamba create --name myenvname bioconductor-segmenter
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-segmenter:<tag> (see `bioconductor-segmenter/tags`_ for valid values for ``<tag>``)