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.
How to install epigrahmm?
biomate-ai/biomate-bioconductor-kb/epigrahmm
$npx -y skills add biomate-ai/biomate-bioconductor-kb --skill epigrahmmInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/biomate-ai/biomate-bioconductor-kb" --skill "biomate-ai/biomate-bioconductor-kb/epigrahmm"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/biomate-ai/biomate-bioconductor-kb" that are relevant to the current task. Run `npx skills add "https://github.com/biomate-ai/biomate-bioconductor-kb"` and select the relevant skills, then follow their instructions.
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