Bio Reporting Automated Qc Reports Agent Skill
Generates standardized quality control reports by aggregating metrics from FastQC, alignment, and other tools using MultiQC. Use when summarizing QC metrics across samples, creating shareable quality reports, or building automated QC pipelines.
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/BioTender-max/awesome-bio-agent-skills --skill bio-reporting-automated-qc-reportsWhat comes with it
5 239 bytes besides the instructionThe instruction itself
8 sections, as written by the authorVersion Compatibility
Reference examples tested with: Cell Ranger 8.0+, FastQC 0.12+, GATK 4.5+, HISAT2 2.2.1+, MultiQC 1.21+, STAR 2.7.11+, Subread 2.0+, bcftools 1.19+, fastp 0.23+, kallisto 0.50+
Before using code patterns, verify installed versions match. If versions differ:
- Python:
pip show <package>thenhelp(module.function)to check signatures - CLI:
<tool> --versionthen<tool> --helpto confirm flags
If code throws ImportError, AttributeError, or TypeError, introspect the installed
package and adapt the example to match the actual API rather than retrying.
Automated QC Reports with MultiQC
"Aggregate QC results into one report" → Combine outputs from FastQC, samtools, Picard, and other tools into a single interactive HTML report.
- CLI:
multiqc .(scans current directory for recognized tool outputs)
Basic Usage
# Aggregate all QC outputs in directory
multiqc results/ -o qc_report/
# Specify output name
multiqc results/ -n my_project_qc
# Include specific tools only
multiqc results/ --module fastqc --module star
Supported Tools
MultiQC recognizes outputs from 100+ bioinformatics tools:
| Category | Tools |
|----------|-------|
| Read QC | FastQC, fastp, Cutadapt |
| Alignment | STAR, HISAT2, BWA, Bowtie2 |
| Quantification | featureCounts, Salmon, kallisto |
| Variant Calling | bcftools, GATK |
| Single-cell | CellRanger, STARsolo |
Configuration
Create multiqc_config.yaml:
title: "RNA-seq QC Report"
subtitle: "Project XYZ"
intro_text: "QC metrics for all samples"
# Custom sample name cleaning
extra_fn_clean_exts:
- '.sorted'
- '.dedup'
# Report sections to include
module_order:
- fastqc
- star
- featurecounts
# Highlight samples
table_cond_formatting_rules:
pct_mapped:
fail: [{lt: 50}]
warn: [{lt: 70}]
Custom Data
# Add custom data file
# File format: sample\tmetric1\tmetric2
multiqc results/ --data-format tsv --custom-data-file custom_metrics.tsv
Python API
from multiqc import run as multiqc_run
# Run programmatically
multiqc_run(analysis_dir='results/', outdir='qc_report/')
Related Skills
- read-qc/quality-reports - Generate input FastQC reports
- read-qc/fastp-workflow - Preprocessing QC
- workflows/rnaseq-to-de - Full workflow with QC
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How to use it
Take biotender-max/bio-reporting-automated-qc-reports from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.