Load when summarising a peak file (BED / narrowPeak) from ATAC-seq / ChIP-seq / CUT&Tag —
Scanned 9/6/2026
Install to Claude Code
npx -y skills add lilinji/GeneTind-Life-Skills --skill genomics-epigenomics --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Genomics Epigenomics?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/lilinji-genomics-epigenomics)More formats (shields.io, HTML) on the badges page.
---
# AUTO-GENERATED header from skill.yaml — do not edit by hand.
# Edit skill.yaml, then run: python scripts/generate_skill_md.py <skill_dir>
name: genomics-epigenomics
description: Load when summarising a peak file (BED / narrowPeak) from ATAC-seq / ChIP-seq / CUT&Tag —
peak count, width distribution, per-chromosome counts, score statistics. Skip when calling peaks from
BAM (run MACS / Genrich externally first); working with single-cell ATAC (use scatac-preprocessing).
version: 0.5.0
author: OmicsClaw
license: MIT
emoji: 🧬
tags:
- genomics
- epigenomics
- atac-seq
- chip-seq
- cut-tag
- peaks
- macs
- bed
requires:
- numpy
- pandas
---
# genomics-epigenomics
## When to use
The user has a peak file (BED, narrowPeak, or broadPeak) from
ATAC-seq, ChIP-seq, or CUT&Tag and wants peak summary statistics:
total peak count, median / mean width, per-chromosome distribution,
optional score column statistics. The script consumes peak files —
it does NOT call peaks from BAM. `--method` (`macs2` / `macs3` /
`homer` / `genrich`) and `--assay` (`chip-seq` / `atac-seq` /
`cut-tag`) are recorded as metadata only.
For single-cell ATAC processing use `scatac-preprocessing`.
## Inputs & Outputs
<!-- AUTO-GENERATED from skill.yaml (interface) — do not edit by hand. Regenerate: python scripts/generate_skill_md.py <skill_dir> -->
**Inputs**
- Modalities: atac-seq, chip-seq
- File types: `.bed`, `.narrowpeak`, `.csv`
**Outputs**
- `tables/peaks_per_chromosome.csv`
- `tables/peaks_summary.csv`
- `report.md`
- `result.json`
## Flow
1. Load peak file (`--input <peaks.bed|narrowPeak>`) or generate a demo at `output_dir/demo_peaks.narrowPeak` (`genomics_epigenomics.py:211`).
2. Parse coordinates; compute per-peak width.
3. Aggregate per-chromosome counts; per-`--assay` expected-width range is added to the report (`genomics_epigenomics.py:172-178`).
4. Write `tables/peaks_summary.csv` (`genomics_epigenomics.py:352`) + `tables/peaks_per_chromosome.csv` (`:360`) + `report.md` + `result.json` (`:366`).
## Gotchas
- **No peak caller is invoked.** This skill summarises an existing BED/narrowPeak file — it does NOT run MACS / Genrich. Run them upstream and feed the output here.
- **`--method` is metadata-only; `--assay` changes the report.** `--method` is recorded in `result.json` only. `--assay` controls the per-assay expected-peak-width range injected into the summary (`genomics_epigenomics.py:172-178`) — `chip-seq` reports 200-2000 bp, `atac-seq` 150-500 bp, `cut-tag` 150-300 bp. Peak parsing itself is identical across assays.
- **`--input` REQUIRED unless `--demo`.** `genomics_epigenomics.py:334` raises `ValueError("--input required when not using --demo")`; non-existent paths raise `FileNotFoundError` at `:337`.
- **3-column BED has no score column.** Without a score (col 5 in BED6 / narrowPeak), the summary statistics for "score" are NaN. Pre-convert to narrowPeak or BED6 for score-aware stats. Note: broadPeak's "signalValue" (col 7) and qValue (col 9) are NOT read — the parser only handles up to BED6 plus the narrowPeak 10-col extension.
- **Coordinate convention is 0-based half-open (BED).** Width = `end - start`. If your input uses 1-based closed coordinates, widths are off-by-one.
- **Demo BED has 500 fixed-pattern peaks.** Useful for orchestrator smoke tests; not biologically meaningful.
## Key CLI
```bash
# Demo
python omicsclaw.py run genomics-epigenomics --demo --output /tmp/epi_demo
# Real ATAC-seq peaks
python omicsclaw.py run genomics-epigenomics \
--input sample_peaks.narrowPeak --output results/ \
--assay atac-seq --method macs3
```
## See also
- `references/parameters.md` — every CLI flag
- `references/methodology.md` — peak-file format conventions, score interpretation
- `references/output_contract.md` — `tables/peaks_summary.csv` + per-chromosome
- Adjacent skills: `scatac-preprocessing` (parallel — single-cell ATAC), `genomics-alignment` (upstream — BAMs feed peak callers), `genomics-qc` (upstream — FASTQ QC before alignment), `bulkrna-de` (parallel — bulk RNA-seq differential expression)
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!