Update to Life Sciences NGS Analysis

{
  "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.",
  "included_files": [
    {
      "relative_path": "agents/openai.yaml",
      "size_in_bytes": 270
    }
  ],
  "skill_md_contents": "---\nname: ngs-atacseq-peaks-qc\ndescription: Run or plan ATAC-seq QC, alignment, TSS enrichment, fragment-size, blacklist, peak-calling, consensus peak, and differential accessibility workflows.\n---\n\n# ATAC-seq Peaks QC\n\nUse 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`.\n\n## Essential Inputs\n\nConfirm:\n\n- FASTQ/BAM inputs and paired-end status\n- organism, genome build, blacklist, and mitochondrial contig names\n- biological replicates, conditions, batches, and sample metadata\n- whether the target is QC only, peaks, consensus peaks, bigWigs, or differential accessibility\n- whether Tn5 shifting is handled by the chosen workflow\n- desired peak caller and downstream matrix generation\n\n## Route\n\nPrefer `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.\n\nPreflight command:\n\n```bash\npython plugins/ngs-analysis/scripts/ngs_preflight.py --pipeline atacseq_peaks_qc --emit-install-plan\n```\n\nFor compact read-level intake/QC, use the shared epigenomics execution package:\n\n```bash\npython plugins/ngs-analysis/scripts/run_fastq_assay_package.py \\\n  --lane epigenomics_peaks \\\n  --sample-sheet atac_samples.csv \\\n  --execute\n```\n\nFor local-light ATAC alignment, peaks, FRiP, TSS, bigWig tracks, and consensus peaks from FASTQ or prepared BAMs, use the dedicated ATAC runner:\n\n```bash\npython plugins/ngs-analysis/scripts/run_atacseq_peaks_qc.py \\\n  --sample-sheet atac_samples.csv \\\n  --bowtie2-index /refs/GRCh38/bowtie2/genome \\\n  --genome-size hs \\\n  --blacklist-bed /refs/GRCh38/blacklists/encode_blacklist.bed \\\n  --tss-bed /refs/GRCh38/tss.bed \\\n  --execute\n```\n\nThis 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.\n\nIt 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.\n\nFor nf-core execution, use `plugins/ngs-analysis/scripts/run_nfcore_pipeline.py --pipeline atacseq`.\n\n## QC Gates\n\nReview before biological interpretation:\n\n- read depth, alignment rate, duplicate rate, and mitochondrial fraction\n- insert-size periodicity/nucleosome pattern\n- TSS enrichment and FRiP score when available\n- blacklist overlap and peak count per sample\n- replicate concordance and consensus peak support\n\nDo not proceed to differential accessibility if replicate quality or metadata is insufficient.\n\n## Outputs\n\nProduce:\n\n- sample sheet and workflow command/profile\n- QC summary and failed-sample flags\n- 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\n- motif summary files when a motif backend is requested\n- differential-accessibility design and contrasts if applicable\n- caveats for low TSS enrichment, high mitochondrial reads, weak replicate concordance, or poor FRiP\n"
}