| name | ngs-atacseq-peaks-qc |
| description | Run or plan ATAC-seq QC, alignment, TSS enrichment, fragment-size, blacklist, peak-calling, consensus peak, and differential accessibility workflows. |
Prerequisite: the plugins/ngs-analysis/ plugin root (its scripts/*.py and references/*.json) is not vendored in this flat vault. Install the ngs-analysis plugin from openai/plugins at the repo root, or every python plugins/ngs-analysis/... command below fails with No such file or directory.
ATAC-seq Peaks QC
Use this skill for ATAC-seq accessibility analysis from FASTQ or BAM. If the assay is ChIP-seq, CUT&RUN, CUT&Tag, or antibody-targeted enrichment, use ngs-chip-cutrun-peaks-qc.
Essential Inputs
Confirm:
- FASTQ/BAM inputs and paired-end status
- organism, genome build, blacklist, and mitochondrial contig names
- biological replicates, conditions, batches, and sample metadata
- whether the target is QC only, peaks, consensus peaks, bigWigs, or differential accessibility
- whether Tn5 shifting is handled by the chosen workflow
- desired peak caller and downstream matrix generation
Route
Prefer nf-core/atacseq for full reproducible processing. Use direct MACS2 only when BAMs are already aligned, duplicate/blacklist handling is known, and the user wants focused peak calling.
Preflight command:
python plugins/ngs-analysis/scripts/ngs_preflight.py --pipeline atacseq_peaks_qc --emit-install-plan
For compact read-level intake/QC, use the shared epigenomics execution package:
python plugins/ngs-analysis/scripts/run_fastq_assay_package.py \
--lane epigenomics_peaks \
--sample-sheet atac_samples.csv \
--execute
For local-light ATAC alignment, peaks, FRiP, TSS, bigWig tracks, and consensus peaks from FASTQ or prepared BAMs, use the dedicated ATAC runner:
python plugins/ngs-analysis/scripts/run_atacseq_peaks_qc.py \
--sample-sheet atac_samples.csv \
--bowtie2-index /refs/GRCh38/bowtie2/genome \
--genome-size hs \
--blacklist-bed /refs/GRCh38/blacklists/encode_blacklist.bed \
--tss-bed /refs/GRCh38/tss.bed \
--execute
This runner emits qc/atacseq_qc_summary.{tsv,json}, qc/atacseq_qc_dashboard.html, native SVG FRiP/peak and insert-size plots, browser-track handoff files under tracks/, and TSS profile/heatmap commands when --tss-bed is supplied. Add --run-motifs --motif-genome <genome> when HOMER motif enrichment should be part of the backend run.
It also emits resources/resource_plan.json, resource_manifest.tsv, resource_env.sh, and resource_readiness.md. The resource check is advisory by default for local-light runs; add --genome-build, --bundle-root <bundle>=<path>, and --require-resource-plan when missing registered reference bundles should block readiness.
For nf-core execution, use plugins/ngs-analysis/scripts/run_nfcore_pipeline.py --pipeline atacseq.
QC Gates
Review before biological interpretation:
- read depth, alignment rate, duplicate rate, and mitochondrial fraction
- insert-size periodicity/nucleosome pattern
- TSS enrichment and FRiP score when available
- blacklist overlap and peak count per sample
- replicate concordance and consensus peak support
Do not proceed to differential accessibility if replicate quality or metadata is insufficient.
Outputs
Produce:
- sample sheet and workflow command/profile
- QC summary and failed-sample flags
- narrowPeak/BED peak sets, consensus peaks, bigWigs, browser-track manifests, browser-track preview HTML, native QC dashboard/SVG plots, TSS plots, and peak-count matrix when requested
- motif summary files when a motif backend is requested
- differential-accessibility design and contrasts if applicable
- caveats for low TSS enrichment, high mitochondrial reads, weak replicate concordance, or poor FRiP
