Description

Functionally profile metagenomic samples using FracMinHash sketches against KEGG database references.

Input

name:type
description
pattern

meta

:map

Groovy Map containing sample information e.g. [ id:'sample1', single_end:false ]

reads

:file

Input metagenomic sequences in FASTA or FASTQ format (can be compressed)

*.{fasta,fastq,fa,fq,fasta.gz,fastq.gz,fa.gz,fq.gz}

ko_sketch

:file

Sourmash signature reference sketch or Sequence Bloom Tree (SBT) of KEGG KOs

*.{sig,sig.zip,sbt.zip}

ksize

:integer

The k-mer size to use for the sketch (typically 7, 11, or 15)

scaled

:integer

The FracMinHash scale factor (e.g., 1000)

Output

name:type
description
pattern

csv

meta

:map

Groovy Map containing sample information e.g. [ id:'sample1', single_end:false ]

*.csv

:file

The main functional abundance profile matrix detailing KEGG Orthology (KO) counts

*.csv

versions_fmhfunprofiler

${task.process}

:string

The name of the process

fmh-funprofiler

:string

The name of the tool

python -c "import importlib.metadata; print(importlib.metadata.version('fmh-funprofiler'))"

:eval

The expression to obtain the version of the tool

Topics

name:type
description
pattern

versions

${task.process}

:string

The name of the process

fmh-funprofiler

:string

The name of the tool

python -c "import importlib.metadata; print(importlib.metadata.version('fmh-funprofiler'))"

:eval

The expression to obtain the version of the tool

Tools

fmhfunprofiler
MIT

fmh-funprofiler is a pipeline that leverages FracMinHash (implemented in sourmash) to functionally profile metagenomic samples, offering a faster and more memory-efficient alternative to alignment-based methods.

github.com/KoslickiLab/fmh-funprofiler 10.1093/bioinformatics/btae397
included in
funcprofiler
maintainer
Github user miraep8
get in touch
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