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Bio Reporting Automated Qc Reports by bg-szy

Name: Bio Reporting Automated Qc Reports
Author: bg-szy

Bio Reporting Automated Qc Reports

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.

bg-szy Updated Sep 17, 2026

File contents

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

---name: bio-reporting-automated-qc-reportsdescription: 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.---# Automated QC Reports with MultiQC## Basic Usage```bash# Aggregate all QC outputs in directorymultiqc results/ -o qc_report/# Specify output namemultiqc results/ -n my_project_qc# Include specific tools onlymultiqc results/ --module fastqc --module star```## Supported ToolsMultiQC 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 |## ConfigurationCreate `multiqc_config.yaml`:```yamltitle: "RNA-seq QC Report"subtitle: "Project XYZ"intro_text: "QC metrics for all samples"# Custom sample name cleaningextra_fn_clean_exts: - '.sorted' - '.dedup'# Report sections to includemodule_order: - fastqc - star - featurecounts# Highlight samplestable_cond_formatting_rules: pct_mapped: fail: [{lt: 50}] warn: [{lt: 70}]```## Custom Data```bash# Add custom data file# File format: sample\tmetric1\tmetric2multiqc results/ --data-format tsv --custom-data-file custom_metrics.tsv```## Python API```pythonfrom multiqc import run as multiqc_run# Run programmaticallymultiqc_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

Frequently asked questions