FastQC MultiQC Read QC Starter

SkillAI & models

Use this skill to run a deterministic read-QC pass with FastQC and aggregate the result with MultiQC on a tiny FASTQ example.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the FastQC MultiQC Read QC Starter skill

About this capability

A framework for discovering, compiling, and validating reusable skills for scientific agents.

What this skill tells your AI

The instructions your AI receives, as published by ma-compbio-lab/skillfoundry in skills/genomics/fastqc-multiqc-read-qc-starter/SKILL.md and read by ahel’s review.

Use this skill to run a deterministic read-QC pass with FastQC and aggregate the result with MultiQC on a tiny FASTQ example.

What it does

  • Runs FastQC on a local FASTQ input from the repo-managed genomics prefix.
  • Forces the prefix bin/ onto PATH so the bundled java runtime is discoverable.
  • Runs MultiQC over the FastQC output directory and writes a compact JSON summary.

When to use it

  • You need a verified starter for sequencing read quality control.
  • You want a minimal example of how FastQC and MultiQC fit together before adding trimming or alignment.
  • You need deterministic summary fields for smoke tests or downstream demos.

Example

python3 skills/genomics/fastqc-multiqc-read-qc-starter/scripts/run_fastqc_multiqc_read_qc.py \
  --input skills/genomics/fastqc-multiqc-read-qc-starter/examples/toy_reads.fastq \
  --summary-out scratch/genomics/fastqc_multiqc_summary.json

Verification

  • Skill-local tests: python3 -m unittest discover -s skills/genomics/fastqc-multiqc-read-qc-starter/tests -p 'test_*.py'
  • Expected summary: total_sequences == 4, gc_percent == 50, and multiqc_sample_count == 1

Signals

GitHub stars
39
Forks
5
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
fastqc-multiqc-read-qc-starter
Source
github.com/ma-compbio-lab/skillfoundry