nf-core pipeline ·
nf-core/funcprofiler
Read-based functional profiling of microbiome short-read sequencing data across multiple profiling tools.
What nf-core/funcprofiler is
nf-core/funcprofiler is a bioinformatics pipeline designed for read-based functional profiling of microbiome sequencing data. Originally developed by Nick Waters, Vini Salazar, Yixuan Yang, and Mirae Baichoo, the workflow coordinates several specialised functional annotation and profiling engines within a standardized Nextflow framework.
The pipeline enables researchers to analyse microbial communities directly from short-read sequences without assembly. By executing chosen profilers against user-provided reference databases, it derives functional information including gene family abundances, pathway abundances, pathway coverages, and antimicrobial resistance profiles.
What the pipeline does
The workflow ingests preprocessed short-read FASTQ files defined in a samplesheet alongside a databases sheet that points to tool-specific reference assets. If a biological sample includes multiple sequencing runs across different accessions, the pipeline merges them before analysis. It then routes the reads through user-selected profiling modules.
Supported modules include HUMANn v3 and HUMANn v4 (using MetaPhlAn alongside HUMANn), FMH FunProfiler for sketch-based profiling, RGI for antimicrobial resistance gene identification, mifaser, and beta modules for DIAMOND blastx alignment and eggNOG-mapper functional annotation.
Key facts
- Pipeline framework
- Nextflow (nf-core)
- Input formats
- FASTQ (short-read), CSV (sample and database sheets)
- Supported profilers
- HUMANn v3, HUMANn v4, FMH FunProfiler, RGI, mifaser, DIAMOND (beta), eggNOG-mapper (beta)
- Primary outputs
- Gene family abundances, pathway abundances, pathway coverage, antimicrobial resistance profiles
- Sequencing platforms
- Short-read platforms (e.g., Illumina)
- Original authors
- Nick Waters, Vini Salazar, Yixuan Yang, Mirae Baichoo
What you can use it for
- Microbial pathway and gene family profiling
- Quantify metabolic pathways and gene families across metagenomic samples using HUMANn v3 or HUMANn v4.
- Antimicrobial resistance profiling
- Identify and profile antimicrobial resistance genes directly from short reads using the Resistance Gene Identifier (RGI).
- Sketch-based functional estimation
- Execute fast, sketch-based functional profiling of short-read metagenomic datasets using FMH FunProfiler.
- Enzyme and functional classification
- Annotate functional capabilities in microbiome samples using mifaser.
Run it here
The research agent runs nf-core/funcprofiler 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 multiple functional profiling and resistance identification tools through a single pipeline interface.
- Automatically concatenates multiple sequencing runs associated with the same biological sample prior to profiling.
- Provides a unified configuration mechanism for managing complex reference databases across different profiling tools.
Watch out for
- Does not support long-read sequencing technologies in the current release.
- Performs no read quality control, adapter trimming, or host sequence decontamination, requiring preprocessed input reads.
- DIAMOND blastx and eggNOG-mapper implementations are in beta and require independent manual review of outputs.
Questions
Can I run nf-core/funcprofiler without my own cluster?
The research agent runs nf-core/funcprofiler 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/funcprofiler under?
MIT, like every nf-core pipeline.
Does the pipeline accept raw sequencing reads directly from the sequencer?
No. The pipeline assumes input FASTQ files have already undergone quality filtering, adapter trimming, and host sequence decontamination, as it performs none of these preprocessing tasks.
Can Oxford Nanopore or PacBio long reads be analysed?
No. Long-read platforms are not supported in this release.
Which databases are required to run HUMANn?
HUMANn runs require four distinct database entities specified in the databases sheet: MetaPhlAn, a nucleotide database (ChocoPhlAn), a protein database (such as UniRef90 DIAMOND), and a utility mapping database.
Are DIAMOND and eggNOG-mapper ready for production use?
Both modules are currently marked as work in progress (beta) and are still undergoing validation for database handling, output structure, and downstream reporting.
How to cite it
Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen. The nf-core framework for community-curated bioinformatics pipelines. Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.
Written from nf-core/funcprofiler's own README. Statements citing a figure that does not appear there are removed before publication. Licence and running details come from our registry.