FastQC MultiQC Read QC Starter
SkillAI & modelsUse 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.
No other account needed.
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
FastQCon a local FASTQ input from the repo-managed genomics prefix. - Forces the prefix
bin/ontoPATHso the bundledjavaruntime is discoverable. - Runs
MultiQCover 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
FastQCandMultiQCfit 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, andmultiqc_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