| 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) or when working with single-cell ATAC (use `scatac-preprocessing`). |
| version | 0.5.0 |
| author | OmicsClaw |
| license | MIT |
| tags | ["genomics","epigenomics","atac-seq","chip-seq","cut-tag","peaks","macs","bed"] |
| requires | ["pandas","numpy"] |
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
| Input | Format | Required |
|---|
| Peaks | .bed (3-col or 6-col) or .narrowPeak (10-col); broadPeak (9-col) loads as BED6 with cols 7-9 dropped | yes (unless --demo) |
| Assay metadata | --assay {chip-seq,atac-seq,cut-tag} (default chip-seq) | no |
| Caller metadata | --method {macs2,macs3,homer,genrich} (default macs2) | no |
| Output | Path | Notes |
|---|
| Peaks summary | tables/peaks_summary.csv | per-peak start/end/width/score |
| Per-chromosome | tables/peaks_per_chromosome.csv | peaks count per chromosome |
| Report | report.md + result.json | always; result.json["data"]["peaks_per_chrom"] mirrors the table |
Flow
- Load peak file (
--input <peaks.bed|narrowPeak>) or generate a demo at output_dir/demo_peaks.narrowPeak (genomics_epigenomics.py:211).
- Parse coordinates; compute per-peak width.
- Aggregate per-chromosome counts; per-
--assay expected-width range is added to the report (genomics_epigenomics.py:172-178).
- 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
python omicsclaw.py run genomics-epigenomics --demo --output /tmp/epi_demo
python omicsclaw.py run genomics-epigenomics \
--input sample_peaks.narrowPeak --output results/ \
--assay atac-seq --method macs3
See also
references/parameters.md — every CLI flagreferences/methodology.md — peak-file format conventions, score interpretationreferences/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)
