ngs-atacseq-peaks-qc

Runs ATAC-seq QC, alignment, peak calling, and differential accessibility workflows from FASTQ or BAM.

5.3k|765|Updated Mar 4, 2026
One-click install
npx skills add https://github.com/openai/plugins --skill ngs-atacseq-peaks-qc
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ngs-atacseq-peaks-qc
Source: https://github.com/openai/plugins/tree/main/plugins/ngs-analysis/skills/ngs-atacseq-peaks-qc
Command: npx skills add https://github.com/openai/plugins --skill ngs-atacseq-peaks-qc

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

ATAC-seq analysis requires coordinating alignment, TSS enrichment, fragment-size checks, blacklist filtering, peak calling, and replicate concordance across many samples, which is error-prone when done ad hoc. This Skill plans and executes that entire workflow with defined QC gates.

Core Features & Use Cases

  • End-to-end ATAC-seq processing: Align FASTQ or BAM inputs, call peaks with MACS2, generate bigWigs, consensus peaks, and browser-track files via a dedicated runner or nf-core/atacseq.
  • QC gating: Produces TSS enrichment, FRiP, insert-size periodicity, mitochondrial fraction, and blacklist overlap metrics with a dashboard and SVG plots before any biological interpretation.
  • Downstream analysis: Supports consensus peak matrices, motif enrichment with HOMER, and differential accessibility design when replicate quality is sufficient.
  • Use Case: Given a sample sheet of paired-end ATAC-seq FASTQs across treatment and control replicates, run the preflight check, execute the local-light runner with a Bowtie2 index and blacklist BED, and review the QC dashboard before calling consensus peaks.

Quick Start

Ask the assistant to plan an ATAC-seq QC and peak-calling workflow from your sample sheet, starting with the preflight command and checking TSS enrichment and FRiP gates.

Frequently Asked Questions about ngs-atacseq-peaks-qc

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run ATAC-seq QC and peak calling from FASTQ files?

Run the dedicated runner script run_atacseq_peaks_qc.py with a sample sheet, Bowtie2 index, genome size, blacklist BED, and TSS BED. It performs alignment, peak calling, FRiP and TSS enrichment, and emits a QC summary, dashboard, bigWigs, and consensus peaks.

Should I use nf-core/atacseq or direct MACS2 for ATAC-seq peak calling?

Prefer nf-core/atacseq for full reproducible processing from raw reads. Use direct MACS2 only when BAMs are already aligned, duplicate and blacklist handling is known, and you want focused peak calling.

What QC metrics matter before ATAC-seq differential accessibility analysis?

Review read depth, alignment rate, duplicate rate, mitochondrial fraction, insert-size nucleosome periodicity, TSS enrichment, FRiP score, blacklist overlap, and replicate concordance. Do not proceed to differential accessibility if replicate quality or metadata is insufficient.

Can this workflow handle ChIP-seq or CUT&RUN data?

No, this Skill is specific to ATAC-seq accessibility analysis. For ChIP-seq, CUT&RUN, CUT&Tag, or antibody-targeted enrichment assays, use the ngs-chip-cutrun-peaks-qc skill instead.

Does the ATAC-seq runner support motif enrichment analysis?

Yes, add the --run-motifs flag with --motif-genome to include HOMER motif enrichment in the backend run. Motif summary files are produced alongside the standard peak and QC outputs.