nf-core pipeline · de-identification, decontamination, edna
nf-core/detaxizer
Identifies and optionally filters specific taxonomic sequences, such as human DNA, from FASTQ sequencing data.
What nf-core/detaxizer is
nf-core/detaxizer is a bioinformatics pipeline designed to detect the presence of specified taxa within genomic and metagenomic FASTQ data and optionally filter those sequences out. It was originally written by Jannik Seidel at the Quantitative Biology Center (QBiC), with assistance from Daniel Straub, and received initial funding from the German Center for Infection Research (DZIF). By default, the workflow targets Homo sapiens sequences for identification and removal.
The pipeline addresses the critical challenge of sequence decontamination and de-identification in microbiome, metagenomic, and environmental DNA (eDNA) research. By separating target host or contaminant reads from the broader sequencing pool, it prevents host DNA contamination from skewing downstream analyses or compromising human genomic privacy. Additionally, the workflow outputs structured samplesheets that integrate with subsequent downstream pipelines, including nf-core/mag and nf-core/taxprofiler.
What the pipeline does
The analysis begins with raw read quality control using FastQC. Users can optionally apply preprocessing via fastp, which carries out adapter trimming, quality cutting, and length or quality filtering. Following read preparation, taxonomic classification is performed using Kraken2, bbduk, or both methods in combination.
If desired, reads identified as matching the target taxon can be further validated using blastn against a reference FASTA database. The pipeline then optionally removes the identified or validated taxonomic subtree from either the raw FASTQ inputs or the preprocessed reads. Finally, execution summaries are compiled alongside quality control outputs into a consolidated MultiQC report.
Key facts
- Pipeline type
- Nextflow workflow
- Latest release
- 1.3.0 (2025-11-14)
- Default target taxon
- Homo sapiens
- Supported inputs
- FASTQ (single-end short reads, paired-end short reads, long reads)
- Quality control tools
- FastQC, fastp, MultiQC
- Classification tools
- Kraken2, bbduk
- Validation tool
- blastn
- Downstream integrations
- nf-core/mag, nf-core/taxprofiler
What you can use it for
- Human Host Decontamination
- Detecting and removing human host reads from clinical microbiome or metagenomic samples prior to public deposition or community analysis.
- Specific Taxon Filtering
- Targeting and eliminating specific organisms or taxonomic subtrees from environmental DNA (eDNA) or shotgun metagenomic sequencing files.
- Dual-Read Type Decontamination
- Processing combined datasets containing both short-read paired-end data and long-read sequencing data in a unified workflow.
- Pre-Assembly Preparation
- Decontaminating metagenomic reads and automatically generating formatted samplesheets for metagenome-assembled genome recovery in nf-core/mag.
Run it here
The research agent runs nf-core/detaxizer with Nextflow on its own machine — up to 32 cores, 256 GiB of memory and 24 hours per run, which covers the test profile and real single-sample runs. It builds the samplesheet, checks it against the pipeline's schema and reads the results back. When a run is too big for one machine, it gives you the exact command for your own cluster instead.
Strengths and limits
Good at
- Supports concurrent processing of short single-end, short paired-end, and long-read FASTQ files within the same samplesheet.
- Provides flexibility between two classification algorithms (Kraken2 and bbduk) with optional blastn validation.
- Allows sequence removal to be executed on either raw input reads or preprocessed reads, or skipped entirely if only identification is needed.
- Outputs downstream samplesheets ready for immediate handoff to nf-core/mag or nf-core/taxprofiler.
Watch out for
- Requires users to supply external FASTA reference files if using bbduk for classification or blastn for read validation.
- Pipeline parameters cannot be supplied through custom configuration files passed with the -c flag and must be specified via CLI or -params-file.
Questions
Can I run nf-core/detaxizer without my own cluster?
The research agent runs nf-core/detaxizer with Nextflow on its own machine — up to 32 cores, 256 GiB of memory and 24 hours per run, which covers the test profile and real single-sample runs. It builds the samplesheet, checks it against the pipeline's schema and reads the results back. When a run is too big for one machine, it gives you the exact command for your own cluster instead.
What licence is nf-core/detaxizer under?
MIT, like every nf-core pipeline.
Which organism does the pipeline target by default?
By default, the pipeline identifies and targets Homo sapiens sequences, though other taxa or taxonomic subtrees can be specified.
Is read removal compulsory when running the pipeline?
No. The pipeline identifies the targeted taxa by default, but actual sequence removal is optional.
What read types can be supplied in the input samplesheet?
The samplesheet accepts single-end short reads, paired-end short reads, and long reads per sample.
Which downstream pipelines can directly consume nf-core/detaxizer outputs?
The pipeline generates dedicated samplesheet directories designed for direct input into nf-core/mag and nf-core/taxprofiler.
How to cite it
Jannik Seidel, Camill Kaipf, Daniel Straub, Sven Nahnsen. nf-core/detaxizer: a benchmarking study for decontamination from human sequences. NAR Genom and Bioinform. 2025;7(3):lqaf125, doi: 10.1093/nargab/lqaf125.
Written from nf-core/detaxizer's own README. Statements citing a figure that does not appear there are removed before publication. Licence and running details come from our registry.