funcprofiler
nf-core/funcprofiler
Read-based functional profiling of microbiome sequencing data
Key tools
Run it
nfclaw run funcprofiler --input samplesheet.csv --outdir results --databases <databases> -profile dockernextflow run pipelines/funcprofiler/upstream -profile docker --input samplesheet.csv --outdir results --databases <databases>nfclaw run funcprofiler --demo --outdir results # adds the upstream test profile (-profile test,docker)Inputs
| column | type | required | allowed values | constraints |
|---|---|---|---|---|
sample | string or integer | yes | matches ^[^\s]+$ | |
run_accession | string or integer | yes | matches ^[^\s]+$ | |
instrument_platform | string | yes | ABI_SOLID, BGISEQ, CAPILLARY, COMPLETE_GENOMICS, DNBSEQ, HELICOS, ILLUMINA, ION_TORRENT, LS454 | |
fastq_1 | string (file path) | yes | matches ^\S+\.f(ast)?q\.gz$ | |
fastq_2 | string (file path) | no | matches ^\S+\.f(ast)?q\.gz$ | |
fasta | string (file path) | no | matches ^\S+\.(fasta|fas|fna|fa)\.gz?$ |
--input must match ^\S+\.csv$.
The samplesheet is a CSV with this header (the columns the schema requires); fill each value per the table above and reference.md (no example value is invented here):
sample,run_accession,instrument_platform,fastq_1Any of the optional columns above may be appended to the header when your data needs them: fastq_2, fasta.
From data files. --input may also be the data files — a directory (searched recursively), a quoted glob, or files (--input once per file) — from which nfclaw writes this samplesheet: sample from file names; fastq_1/fastq_2 from FastQ files (mates paired by _R1/_R2, or by _1/_2 when their read names show they are mates); fasta from files matching their patterns, by sample name. Set the required columns no file determines with --sheet-set COLUMN=VALUE (a constant or a {sample}/{lane} template): run_accession (matching ^[^\s]+$); instrument_platform (one of ABI_SOLID, BGISEQ, CAPILLARY, COMPLETE_GENOMICS, DNBSEQ, HELICOS, ILLUMINA, ION_TORRENT, LS454). Preview it with --check; a run records it in <outdir>/provenance/ for replay.
Resources
Resource requests follow the pipeline's configs and selected profiles. nf-core's resource labels often assume a server — a single step can request far more memory than a workstation has, and retry rules can increase requests. If a run fails with Process requirement exceeds available memory (or CPUs), cap every request, and every retry, at what this machine actually has:
nfclaw run funcprofiler --input samplesheet.csv --outdir results --databases <databases> -profile docker \ --limit-cpus 4 --limit-memory 15.GBnfclaw turns those into Nextflow's process.resourceLimits and passes them as a -c config — the mechanism nf-core prescribes for exactly this (docs). Set them to the machine's real capacity. --limit-time DURATION also caps how long any one task may run: a task that needs longer is stopped, and so is every retry, so set it only as a deliberate ceiling, never as a guess at how long the analysis takes. The generated config is kept in <outdir>/provenance/, so commands.sh replays the run under the same ceiling.
Nextflow engine
This release declares nextflowVersion = '!>=25.10.4'.
To pin this release's declared minimum engine — useful when a newer Nextflow has incompatible config parsing:
nfclaw run funcprofiler ... --nxf-ver 25.10.4--nxf-ver is recorded in <outdir>/provenance/, so the replay uses the same engine. See known-issues.
Demo
nfclaw run funcprofiler --demo --outdir results # adds the upstream test profile (-profile test,docker)Samplesheet
A CSV with this header (the columns the schema requires). Fill each value per the constraints below; optional columns from the table may be appended.
sample,run_accession,instrument_platform,fastq_1| Column | Type | Required | Allowed / constraints |
|---|---|---|---|
sample | string or integer | required | matches ^[^\s]+$ |
run_accession | string or integer | required | matches ^[^\s]+$ |
instrument_platform | string | required | ABI_SOLIDBGISEQCAPILLARYCOMPLETE_GENOMICSDNBSEQHELICOSILLUMINAION_TORRENTLS454 |
fastq_1 | string (file path) | required | matches ^\S+\.f(ast)?q\.gz$ |
fastq_2 | string (file path) | optional | matches ^\S+\.f(ast)?q\.gz$ |
fasta | string (file path) | optional | matches ^\S+\.(fasta|fas|fna|fa)\.gz?$ |
Required parameters
--inputstring (file path)Path to comma-separated file containing information about the samples in the experiment.
Constraint · matches ^\S+\.csv$
--databasesstring (file path)Path to comma-separated file containing information about databases and profiling parameters for each taxonomic profiler
Constraint · matches ^\S+\.csv$
--outdirstring (directory path)The output directory where the results will be saved. You have to use absolute paths to storage on Cloud infrastructure.
Parameter explorer
34 parameters · 4 groupsEvery parameter from the pinned nextflow_schema.json. nfclaw checks explicit values before launch; complex rules use the pinned pipeline's runtime validation. Search, filter by group, and expand any parameter for its default, allowed values and constraints.
17 parameters · 17 hidden
Generic options4
Display the help message.
Display the full detailed help message.
Custom MultiQC yaml file containing HTML including a methods description.
Display hidden parameters in the help message (only works when --help or --help_full are provided).
Input Output options6
Path to comma-separated file containing information about databases and profiling parameters for each taxonomic profiler
Email address for completion summary.
Path to comma-separated file containing information about the samples in the experiment.
MultiQC report title. Printed as page header, used for filename if not otherwise specified.
The output directory where the results will be saved. You have to use absolute paths to storage on Cloud infrastructure.
Specify to save decompressed user-supplied TAR archives of databases
Profiling options7
Turn on translated alignment with DIAMOND blastx. Requires a diamond-tagged database to be present in the CSV file passed to --databases
Turn on functional annotation with eggNOG-mapper. Requires eggnogmapper-tagged database entries to be present in the CSV file passed to --databases
Turn on profiling with FMH FunProfiler. Requires a fmhfunprofiler-tagged database to be present in the CSV file passed to --databases
Turn on profiling with HUMAnN3. Requires a humann_v3-tagged database to be present in the CSV file passed to --databases
Turn on profiling with HUMAnN4. Requires a humann_v4-tagged database to be present in the CSV file passed to --databases
Turn on profiling with mi-faser. Requires a mifaser-tagged database to be present in the CSV file passed to --databases
Turn on profiling with RGI. Requires a rgi-tagged database to be present in the CSV file passed to --databases
Outputs
Results land in --outdir; the files and directory layout depend on the selected workflow, parameters and publication settings. Run metadata is normally placed in <outdir>/pipeline_info/ (execution report, software versions), when those outputs are enabled. The pinned tree includes MultiQC support; a report is produced only when its workflow step runs. nfclaw run also writes <outdir>/provenance/ with the exact params file and the run log, <outdir>/provenance/logs/run.log — the whole launch, whose last line states the outcome (Nextflow's own log is <outdir>/.nextflow.log); unless --no-provenance it adds a run manifest (pinned version, commit and exact command), input/output SHA-256 checksums, and a replayable commands.sh.
The exact output files and directory layout for this release are documented upstream: github.com/nf-core/funcprofiler/blob/1.0.0/docs/output.md
Check a run — in the foreground or the background — with nfclaw status <outdir>: success, still running, how it ended (with the error), or stopped without an outcome; exit 0 success, 3 running, 1 otherwise.