Version Compatibility

Reference 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:

• 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.

Contamination Screening

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.

• CLI: fastq_screen --conf fastq_screen.conf reads.fq

FastQ Screen Overview

FastQ Screen aligns a subset of reads against multiple reference genomes to identify:

• Cross-species contamination
• Bacterial/viral contamination
• Adapter sequences
• PhiX spike-in
• Sample swaps

Basic Usage

bash
# 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

Configuration File

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

Pre-built Databases

bash
# Download common screening databases
fastq_screen --get_genomes

# Downloads to ~/fastq_screen_databases/
# Includes: Human, Mouse, Rat, E.coli, PhiX, Adapters, etc.

Screening Options

bash
# 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

Output Options

bash
# 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

Filter Codes

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 |

bash
# 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

Output Files

| File | Description | |------|-------------| | *_screen.txt | Tab-delimited results | | *_screen.png | Visualization | | *_screen.html | HTML report |

Results Format

#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

Interpreting Results

Expected Results by Sample Type

| 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 |

Common Issues

| 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 |

MultiQC Integration

FastQ Screen results are automatically detected by MultiQC:

bash
# Screen all samples
for f in *.fastq.gz; do
    fastq_screen --outdir screen_results/ "$f"
done

# Aggregate with MultiQC
multiqc screen_results/

Custom Database Setup

Create Bowtie2 Index

bash
# Index a FASTA file
bowtie2-build reference.fa reference

# Add to config
# DATABASE	MyGenome	/path/to/reference

Common Databases to Include

| 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 |

Example Workflows

Standard Screening

bash
# Download databases
fastq_screen --get_genomes

# Screen samples
fastq_screen --outdir screen_results/ --threads 8 *.fastq.gz

# Check results
multiqc screen_results/

Remove Contamination

bash
# 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

Related Skills

• quality-reports - FastQC shows overrepresented sequences
• adapter-trimming - Remove adapter contamination
• metagenomics/kraken-classification - Deeper taxonomic analysis