biotender-max/bio-read-qc-contamination-screening
Detect sample contamination and cross-species reads using FastQ Screen. Screen reads against multiple reference genomes to identify bacterial, viral, adapter, or sample swap contamination. Use when suspecting cross-contamination or working with samples prone to microbial contamination.
npx skills add https://github.com/BioTender-max/awesome-bio-agent-skills --skill bio-read-qc-contamination-screeningReference examples tested with: BBTools 39.0+, Bowtie2 2.5.3+, FastQ Screen 0.15+, FastQC 0.12+, MultiQC 1.21+
Before using code patterns, verify installed versions match. If versions differ:
<tool> --version then <tool> --help to confirm flagsIf code throws ImportError, AttributeError, or TypeError, introspect the installed
package and adapt the example to match the actual API rather than retrying.
Screen FASTQ files against multiple genomes to identify contamination sources using FastQ Screen.
"Check for contamination in sequencing data" → Align a sample of reads against multiple reference genomes to identify cross-species or cross-sample contamination.
fastq_screen --conf fastq_screen.conf reads.fqFastQ Screen aligns a subset of reads against multiple reference genomes to identify:
# Screen against configured genomes
fastq_screen sample.fastq.gz
# Multiple files
fastq_screen *.fastq.gz
# Specify output directory
fastq_screen --outdir qc_results/ sample.fastq.gz
# Custom config file
fastq_screen --conf my_screen.conf sample.fastq.gz
Create fastq_screen.conf:
# Database locations
DATABASE Human /path/to/human/genome
DATABASE Mouse /path/to/mouse/genome
DATABASE Ecoli /path/to/ecoli/genome
DATABASE PhiX /path/to/phix/genome
DATABASE Adapters /path/to/adapters
DATABASE rRNA /path/to/rrna
# Aligner (bowtie2 recommended)
BOWTIE2 /path/to/bowtie2
# Or use BWA
# BWA /path/to/bwa
# Threads
THREADS 8
# Download common screening databases
fastq_screen --get_genomes
# Downloads to ~/fastq_screen_databases/
# Includes: Human, Mouse, Rat, E.coli, PhiX, Adapters, etc.
# Number of reads to sample (default 100000)
fastq_screen --subset 200000 sample.fastq.gz
# Use all reads (slow)
fastq_screen --subset 0 sample.fastq.gz
# Set threads
fastq_screen --threads 8 sample.fastq.gz
# Paired-end (screen R1 only by default)
fastq_screen sample_R1.fastq.gz
# Force screening both pairs
fastq_screen --paired sample_R1.fastq.gz sample_R2.fastq.gz
# Generate PNG plot (default)
fastq_screen sample.fastq.gz
# No plot (text only)
fastq_screen --nograph sample.fastq.gz
# Generate additional mapping statistics
fastq_screen --tag sample.fastq.gz
# Filter reads by mapping (keep unmapped to all genomes)
fastq_screen --filter 0000 sample.fastq.gz
# Keep only reads mapping to first genome (e.g., Human)
fastq_screen --filter 1--- sample.fastq.gz
Use --filter to select reads based on mapping status:
| Code | Meaning |
|------|---------|
| 0 | Did not map to genome |
| 1 | Mapped uniquely |
| 2 | Mapped more than once |
| 3 | Mapped (unique or multi) |
| - | Ignore this genome |
# Example: Keep reads mapping only to Human (first genome)
# Human:1, all others:0
fastq_screen --filter 10000 sample.fastq.gz
# Keep reads NOT mapping to anything (clean reads)
fastq_screen --filter 00000 sample.fastq.gz
| File | Description |
|------|-------------|
| *_screen.txt | Tab-delimited results |
| *_screen.png | Visualization |
| *_screen.html | HTML report |
#Fastq_screen version: 0.15.3
Genome #Reads_processed #Unmapped %Unmapped #One_hit_one_genome %One_hit_one_genome #Multiple_hits_one_genome %Multiple_hits_one_genome #One_hit_multiple_genomes %One_hit_multiple_genomes Multiple_hits_multiple_genomes %Multiple_hits_multiple_genomes
Human 100000 2000 2.00 95000 95.00 1000 1.00 1500 1.50 500 0.50
Mouse 100000 98000 98.00 100 0.10 50 0.05 1500 1.50 350 0.35
| Sample Type | Expected Pattern |
|-------------|------------------|
| Human sample | >90% Human, <1% others |
| Mouse sample | >90% Mouse, <1% others |
| Human + PhiX | >80% Human, ~10% PhiX |
| Contaminated | Significant % to unexpected genome |
| Pattern | Likely Cause |
|---------|--------------|
| High adapter % | Library prep issue |
| High PhiX % | Spike-in not removed |
| High E.coli % | Bacterial contamination |
| High rRNA % | rRNA depletion failed |
| Multiple species | Sample swap or contamination |
FastQ Screen results are automatically detected by MultiQC:
# Screen all samples
for f in *.fastq.gz; do
fastq_screen --outdir screen_results/ "$f"
done
# Aggregate with MultiQC
multiqc screen_results/
# Index a FASTA file
bowtie2-build reference.fa reference
# Add to config
# DATABASE MyGenome /path/to/reference
| Genome | Purpose |
|--------|---------|
| Human (GRCh38) | Human samples |
| Mouse (GRCm39) | Mouse samples |
| E. coli | Bacterial contamination |
| PhiX | Illumina spike-in |
| Adapters | Library prep |
| rRNA | Ribosomal RNA |
| Vectors | Cloning vectors |
| Mycoplasma | Cell culture contamination |
# Download databases
fastq_screen --get_genomes
# Screen samples
fastq_screen --outdir screen_results/ --threads 8 *.fastq.gz
# Check results
multiqc screen_results/
# Screen and tag reads
fastq_screen --tag sample.fastq.gz
# Filter to keep only Human reads (assuming Human is first database)
fastq_screen --filter 3----- --tag sample.fastq.gz
# Or use BBDuk for removal
bbduk.sh in=sample.fastq.gz out=clean.fastq.gz \
ref=contaminants.fa k=31 hdist=1
Take biotender-max/bio-read-qc-contamination-screening 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.