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metagenome-functional-profiling

Skill4 starsChanged 12 days agoMITView on GitHub

Functional annotation of metagenomic data using HUMAnN 3 for pathway abundance, Prokka for gene prediction, and eggNOG-mapper for ortholog assignment.

The file

We split this skill into the rules it gives an agent

3 rules. About 0 are common, 1 is distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    If HUMAnN: run humann with --input FASTQs, optionally with --taxonomic-profile for guided search.

    line 29
  2. Distinctive:

    If Prokka: run on contigs/MAGs for gene prediction and annotation.

    line 32
  3. Very specific:

    If eggNOG-mapper: run emapper.py on predicted protein sequences for COG/KEGG/GO annotation.

    line 33

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Skill: metagenome-functional-profiling

Use When

  • The user wants to know what metabolic functions are present in a metagenome.
  • The user needs pathway-level abundance profiles (MetaCyc, KEGG).
  • The user wants to annotate predicted genes from MAGs or assembled contigs.
  • The user needs gene family and ortholog group assignments.

Inputs

  • Required:
    • Host-depleted FASTQ file(s) for HUMAnN, OR assembled contigs/MAGs FASTA for Prokka/eggNOG.
  • Optional:
    • --tool STR — Tool to use: humann, prokka, or eggnog (default: humann).
    • --db PATH — HUMAnN databases (ChocoPhlAn, UniRef) or eggNOG database path.
    • --taxonomic-profile FILE — Taxonomic profile from metagenome-taxonomic-profiling to speed up HUMAnN.
    • --kingdom STR — Prokka kingdom (default: Bacteria).
    • --threads N — Number of threads (default: 4).
    • --outdir DIR — Output directory (default: functional_profiling_results).

Workflow

  1. If HUMAnN: run humann with --input FASTQs, optionally with --taxonomic-profile for guided search.
  2. HUMAnN produces: gene families (RPK), pathway abundance, pathway coverage.
  3. Normalize HUMAnN output with humann_renorm_table (CPM or relative abundance).
  4. If Prokka: run on contigs/MAGs for gene prediction and annotation.
  5. If eggNOG-mapper: run emapper.py on predicted protein sequences for COG/KEGG/GO annotation.
  6. Report: number of gene families, pathways detected, top abundant pathways, functional category distribution.

Output Contract

  • HUMAnN gene family table — Gene families with RPK values (<outdir>/<sample>_genefamilies.tsv).
  • HUMAnN pathway abundance table — Pathway abundances (<outdir>/<sample>_pathabundance.tsv).
  • HUMAnN pathway coverage table — Pathway coverage scores (<outdir>/<sample>_pathcoverage.tsv).
  • Prokka annotations — GFF, GBK, FAA, FFN files (<outdir>/prokka/).
  • eggNOG annotation table — COG, KEGG, GO annotations (<outdir>/eggnog/<sample>.emapper.annotations).
  • Functional summary — Top pathways, gene family counts, functional category distribution (<outdir>/functional_summary.txt).

Limits

  • HUMAnN 3 requires ChocoPhlAn (approximately 15 GB) and UniRef90 (approximately 20 GB) databases.
  • Prokka is designed for prokaryotic genomes; use appropriate --kingdom for archaea.
  • eggNOG database is approximately 45 GB.
  • HUMAnN is computationally intensive and may take hours per sample; for large cohorts, consider running on HPC.
  • HUMAnN, Prokka, and eggNOG-mapper must be installed and available on $PATH.
  • Prokka and eggNOG-mapper operate on contigs/proteins, not raw reads.
  • Common failure cases:
    • HUMAnN ChocoPhlAn or UniRef databases not downloaded or path misconfigured.
    • Prokka failing on non-prokaryotic contigs when --kingdom is set incorrectly.
    • eggNOG-mapper database version mismatch with the installed emapper version.

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