known-motif-enrichment
This skill should be used when users need to perform known motif enrichment analysis on ChIP-seq, ATAC-seq, or other genomic peak files using HOMER (Hypergeometric Optimization of Motif EnRichment). It identifies enrichment of known transcription factor binding motifs from established databases in genomic regions.
npx skills add majiayu000/claude-skill-registry --skill 13-toolbased-known-motif-enrichment --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# HOMER Known Motif Enrichment ## Overview This skill enables comprehensive known motif enrichment analysis using HOMER tools for genomic peak files. It identifies enrichment of known transcription factor binding motifs from established databases in genomic regions. --- ## When to use this skill Use this skill when you need to uncover the enrichment of a certain motif in the promoter regions of a set of genes, or directly from a set of genomic regions, such as peaks from ChIP-seq or ATAC-seq, with prior assumptions about which transcription factors are involved. Typical use cases include: - Calculate the enrichment of a certain motif in the whole genome or in specific genomic regions, like promoters of a gene list or peaks from ChIP-seq or ATAC-seq. --- ## Inputs & Outputs ### Inputs Input files should be in one of the following formats: - **BED files**: Standard genomic interval format - **narrowPeak**: narrow peak format - **broadPeak**: broad peak format - **gene list**: A list of genes provided by user or generated in previous analysis. May end with `.txt`, `.tsv`, `.csv`, etc. ### Outputs ```bash ${sample}_known_motif_enrichment/ results/ homerResults.html # De novo motif disc
- Overview
- When to use this skill
- Inputs & Outputs
- Inputs
- Outputs
- Decision Tree
- Step 0 — Gather Required Information from the User
- Step 1: Initialize Project
- Step 2: Prepare genome file for homer
- Step 3 (Optional): Standardize chromosome names for BED files
- Step 4: Locate motif file for a certain TF
- Quality Control and Best Practices
- Important Metrics
results/ homerResults.html # De novo motif discovery results seq.autonorm.tsv # Sequence composition statistics motifFindingParameters.txt # Parameters used for analysis homerMotifs.all.motifs homerMotifs.motifs12 homerMotifs.motifs10 homerMotifs.motifs8 nonRedundant.motifs homerResults/
What does the known-motif-enrichment skill do?
This skill should be used when users need to perform known motif enrichment analysis on ChIP-seq, ATAC-seq, or other genomic peak files using HOMER (Hypergeometric Optimization of Motif EnRichment). It identifies enrichment of known transcription factor binding motifs from established databases in genomic regions.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill 13-toolbased-known-motif-enrichment --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.