Built for methylation and chromatin accessibility analysis when you're working with long-format CpG data, ChIP-seq peaks, or ATAC-seq files. Combines pandas and scipy with genome annotation tools to handle the annoying parts: coordinate system mismatches, CpG density calculations that trip up on row versus unique-site counting, and differential methylation with proper FDR correction. The bundled methylation_density.py script is there because computing genome-wide average chromosomal density by hand always ends up wrong the first time. Useful if you're filtering bisulfite data or running chi-square tests on chromatin state distributions. The top-of-mind rules about long-format CSVs suggest this was written after several painful debugging sessions.
npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-epigenomics