Imported from openai/plugins (plugins/ngs-analysis/skills/ngs-atacseq-peaks-qc/SKILL.md). Install upstream with npx skills add openai/plugins --skill ngs-atacseq-peaks-qc. Copyright stays with the author.

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