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ngs-atacseq-peaks-qc Skill

AI Agent SkillJavaScriptOpen source

Run or plan ATAC-seq QC, alignment, TSS enrichment, fragment-size, blacklist, peak-calling, consensus peak, and differential accessibility workflows. Published by openai in plugins.

Decision snapshot

Is this a fit?

Best for

Data analysis, Includes SKILL.md, Reusable instructions

Works with

Compatibility not yet detected.

Access

Permission behavior not yet detected.

Setup

Copy skill directory

Project health

19 days ago

Considerations

No specific cautions were detected. Review the source and requested permissions before installing.

What is ngs-atacseq-peaks-qc Skill?

Run or plan ATAC-seq QC, alignment, TSS enrichment, fragment-size, blacklist, peak-calling, consensus peak, and differential accessibility workflows. Published by openai in plugins. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.

Trust signal
95/100
Maintenance signal
90/100
Adoption signal
92/100

Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement. See how SkillIndex evaluates profiles.

Key capabilities

  • Includes SKILL.md support
  • Reusable instructions support
  • Data analysis
  • Data analysis use cases

Declared skill metadata

  • Source file: plugins/ngs-analysis/skills/ngs-atacseq-peaks-qc/SKILL.md

These fields retain source and confidence evidence from the indexed SKILL.md.

Compatibility and setup

Copy skill directory
  • Install or run with Copy skill directory

When to use ngs-atacseq-peaks-qc Skill

  • Use it for data analysis.

Built with

JavaScriptCopy skill directory

Editorial notes

Source

  • Creator: openai
  • Repository: openai/plugins
  • Skill file: plugins/ngs-analysis/skills/ngs-atacseq-peaks-qc/SKILL.md

What it does

Run or plan ATAC-seq QC, alignment, TSS enrichment, fragment-size, blacklist, peak-calling, consensus peak, and differential accessibility workflows.

Skill instructions

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: bash python plugins/ngs-analysis/scripts/ngspreflight.py --pipeline atacseqpeaksqc --emit-install-plan For compact read-level intake/QC, use the shared epigenomics execution package

Verified compatibility and discovery

Frequently asked questions

What is ngs-atacseq-peaks-qc?

ngs-atacseq-peaks-qc is a open-source AI agent skill with Copy skill directory. Run or plan ATAC-seq QC, alignment, TSS enrichment, fragment-size, blacklist, peak-calling, consensus peak, and differential accessibility workflows.

Who is ngs-atacseq-peaks-qc best for?

ngs-atacseq-peaks-qc is best for reusing agent instructions, scripts, and references, data analysis workflows.

How do I install ngs-atacseq-peaks-qc?

Install or run ngs-atacseq-peaks-qc using Copy skill directory. Check ngs-atacseq-peaks-qc for the latest setup command.

Is ngs-atacseq-peaks-qc actively maintained?

ngs-atacseq-peaks-qc may need a closer maintenance check before production use.

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Last commit
19 days ago
Last verified
Aug 24, 2026
Metadata fetched
Aug 24, 2026
Repository age
6 months
License
Unknown

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Review this source-backed profile, send a correction with evidence, or link to it from your documentation. Claims verify your relationship to the project; profile facts still require source evidence and editorial review.

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