recipe bioconductor-ebseqhmm

Bayesian analysis for identifying gene or isoform expression changes in ordered RNA-seq experiments






The EBSeqHMM package implements an auto-regressive hidden Markov model for statistical analysis in ordered RNA-seq experiments (e.g. time course or spatial course data). The EBSeqHMM package provides functions to identify genes and isoforms that have non-constant expression profile over the time points/positions, and cluster them into expression paths.

package bioconductor-ebseqhmm

(downloads) docker_bioconductor-ebseqhmm



depends bioconductor-ebseq:


depends r-base:




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-ebseqhmm

and update with::

   mamba update bioconductor-ebseqhmm

To create a new environment, run:

mamba create --name myenvname bioconductor-ebseqhmm

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull<tag>

(see `bioconductor-ebseqhmm/tags`_ for valid values for ``<tag>``)

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