bio-read-qc-quality-reports

FreedomIntelligence/OpenClaw-Medical-SkillsBiology Medicine and BioinformaticsAudit pendingSnapshot 456dba7d0a33

Summary

This source did not publish a separate summary. Review SKILL.md before using the skill.

SKILL.md

Version Compatibility

Reference examples tested with: pandas 2.2+

Before using code patterns, verify installed versions match. If versions differ:

Python: pip show <package> then help(module.function) to check signatures
CLI: <tool> --version then <tool> --help to 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.

Quality Reports

Generate quality reports for FASTQ files using FastQC and aggregate multiple reports with MultiQC.

"Run quality control on FASTQ files" → Generate per-base quality, adapter content, and duplication plots, then aggregate across samples.

CLI: fastqc *.fastq.gz then multiqc .

FastQC - Single Sample Reports

Basic Usage

# Single file
fastqc sample.fastq.gz

# Multiple files
fastqc *.fastq.gz

# Specify output directory
fastqc -o qc_reports/ sample_R1.fastq.gz sample_R2.fastq.gz

# Set threads
fastqc -t 4 *.fastq.gz

Output Files

FastQC produces two files per input:

sample_fastqc.html - Interactive HTML report
sample_fastqc.zip - Data files and images

Key Modules

Module	What It Shows	Warning Signs
Per base sequence quality	Quality scores across read	Drop below Q20 at 3' end
Per sequence quality	Quality score distribution	Bimodal distribution
Per base sequence content	Nucleotide composition

# Unzip to access raw data
unzip sample_fastqc.zip

# View summary
cat sample_fastqc/summary.txt

# Get per-base quality
cat sample_fastqc/fastqc_data.txt | grep -A 50 ">>Per base sequence quality"

# Aggregate all FastQC reports in current directory
multiqc .

# Specify input and output
multiqc qc_reports/ -o multiqc_output/

# Custom report name
multiqc . -n my_project_qc

# Force overwrite
multiqc . -f

# Flat directory (no sample subdirs)
multiqc --flat .

# Export data as TSV
multiqc . --export

# Only specific modules
multiqc . -m fastqc

# Exclude patterns
multiqc . --ignore '*_trimmed*'

# Include patterns
multiqc . --ignore-samples '*negative*'

import pandas as pd

general_stats = pd.read_csv('multiqc_data/multiqc_general_stats.txt', sep='\t')
print(general_stats.columns)

fastqc_data = pd.read_csv('multiqc_data/multiqc_fastqc.txt', sep='\t')

# All FASTQ files in parallel
fastqc -t 8 -o qc_reports/ raw_data/*.fastq.gz

# Then aggregate
multiqc qc_reports/ -o multiqc_output/

# Create separate directories
mkdir -p qc_reports/raw qc_reports/trimmed

# QC raw reads
fastqc -o qc_reports/raw/ raw_data/*.fastq.gz

# After trimming (using fastp, cutadapt, etc.)
fastqc -o qc_reports/trimmed/ trimmed_data/*.fastq.gz

# Compare with MultiQC
multiqc qc_reports/ -o qc_comparison/

Phred Score	Error Rate	Interpretation
Q40	0.0001	Excellent
Q30	0.001	Good (Illumina target)
Q20	0.01	Acceptable
Q10	0.1	Poor

Issue	Likely Cause	Action
Low quality at 3' end	Normal degradation	Trim 3' end
Adapter contamination	Short inserts	Trim adapters
GC bias	Library prep	Consider correction
High duplication	Low complexity, PCR	Mark/remove duplicates
Overrepresented seqs	Adapters, primers	Check sequences

Custom_Adapter_Name    ACGTACGTACGT

# Warn if mean quality below 25
quality_sequence    warn    25
quality_sequence    error   20

bio-read-qc-quality-reports

Summary

SKILL.md

Version Compatibility

Quality Reports

FastQC - Single Sample Reports

Basic Usage

Output Files

Key Modules

Extract Data from ZIP

MultiQC - Aggregate Reports

Basic Usage

Common Options

Output Files

Extract Data Programmatically

Batch Processing

Process Multiple Samples

Before and After Trimming

Interpretation Guide

Quality Scores

Common Issues

Configuration

Custom Adapters

Custom Limits

Related Skills

Related skills