bio-reporting-automated-qc-reports
Automated QC Reports with MultiQC
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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