nf-core pipeline · biosurveillance, pathogen-identification
nf-core/pathogensurveillance
A population genomics pipeline for pathogen identification, variant detection, and phylogenetic biosurveillance.
What nf-core/pathogensurveillance is
nf-core/pathogensurveillance is a population genomics workflow for pathogen identification, variant detection, and biosurveillance across eukaryotic and prokaryotic organisms. Developed by Zachary S.L. Foster, Martha Sudermann, Camilo Parada-Rojas, Logan K. Blair, Fernanda I. Bocardo, Ricardo Alcalá-Briseño, Hung Phan, Nicholas C. Cauldron, Alexandra J. Weisberg, Jeff H. Chang, and Niklaus J. Grünwald, the workflow automates the genomic characterisation and contextual placement of uncharacterised isolates.
Genomic diagnosticians frequently encounter unknown samples where reference genomes are not known beforehand. Manually identifying and retrieving the correct reference genome requires specialist technical skill and can slow down surveillance efforts. nf-core/pathogensurveillance addresses this challenge by automatically selecting and downloading suitable reference genomes from public databases, enabling reliable exploratory population genomics with minimal user input.
What the pipeline does
The pipeline ingests raw genomic DNA sequencing reads from short-read or long-read platforms. Reads are assembled into genomes, and k-mer sketches (compact DNA fingerprints) are calculated from the assemblies. Using sourmash, these sketches are matched against a reference fingerprint library to identify closely related genomes, which are then automatically retrieved from NCBI RefSeq.
Following reference discovery, the pipeline performs rapid initial taxonomic classification using k-mer sketches, followed by a multi-gene phylogeny and single-nucleotide polymorphism (SNP)-based phylogenetic tree construction. Results and publication-quality visualisations are compiled into an interactive HTML summary report for user-defined sample groupings.
Key facts
- Workflow framework
- Nextflow DSL2
- Pipeline release
- 1.1.0
- Input data
- Raw genomic DNA FASTQ reads (short-read and long-read)
- Taxonomic scope
- Prokaryotes and eukaryotes (pathogens and non-pathogens)
- Reference source
- NCBI RefSeq
- Reference finder
- sourmash
- Main output
- Interactive HTML report and phylogenetic figures
What you can use it for
- Unknown pathogen identification
- Determining the species identity of unknown bacterial or eukaryotic isolates directly from raw genomic DNA reads without requiring prior knowledge of a reference genome.
- Phylogenetic outbreak surveillance
- Constructing multi-gene and SNP-based phylogenies to trace evolutionary relationships and variant profiles across collected disease isolates.
- Exploratory non-pathogen genomics
- Carrying out automated assembly, reference matching, and phylogenetic placement on non-pathogenic eukaryotic or bacterial genomic DNA.
- Incremental cohort analysis
- Re-analysing cohorts by supplying cached prior runs and appending newly sequenced samples to an existing phylogenetic dataset.
Run it here
The research agent runs nf-core/pathogensurveillance 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
- Automatically discovers and downloads reference assemblies from NCBI RefSeq using sourmash k-mer sketching.
- Requires only a simple CSV samplesheet listing raw read paths to run a full analysis.
- Accommodates both short-read and long-read genomic DNA technologies for eukaryotic and prokaryotic organisms.
- Delivers results as an interactive HTML report containing publication-ready figures.
Watch out for
- Does not support viral sequencing datasets.
- Cannot process non-genomic DNA inputs such as RNA-seq, ChIP-seq, RAD-seq, or pre-assembled FASTA sequences.
- Not intended for mixed or impure biological samples.
- Unsuited to specialised population genetics analyses that require extensive manual parameter adjustment at each stage.
Questions
Can I run nf-core/pathogensurveillance without my own cluster?
The research agent runs nf-core/pathogensurveillance 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/pathogensurveillance under?
MIT, like every nf-core pipeline.
What is the minimum input required to run the pipeline?
The minimum input is a CSV file containing a single column with file paths to raw genomic DNA sequencing reads.
Can the pipeline process viral samples or metagenomic mixtures?
No. The pipeline is explicitly not designed for viral sequence data or mixed, impure samples.
How does the pipeline choose reference genomes for unidentified samples?
It generates k-mer sketches from assembled reads and matches them against an extensive reference library using sourmash, then downloads matching references directly from NCBI RefSeq.
Is the pipeline restricted to pathogenic organisms?
No. The pipeline also functions with non-pathogenic eukaryotic and prokaryotic genomic DNA samples.
How to cite it
Foster, ZSL, Sudermann, MA, Parada Rojas, CH, Blair, LK, Iruegas Bocardo, F, Dhakal, U, Weisberg, AJ, Phan, H, Chang, JH, Grunwald, NJ. Pathogensurveillance: an automated pipeline for population genomic analyses and pathogen identification. BioRxiv 2025 2025.10.31.685798. doi: https://doi.org/10.1101/2025.10.31.685798
Written from nf-core/pathogensurveillance's own README. Statements citing a figure that does not appear there are removed before publication. Licence and running details come from our registry.