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bio-protein-clustering-pangenome

Cluster proteins from FASTAs into pan-genome presence/absence matrices using MMseqs2 or ProteinOrtho.

7|1|Updated Feb 2, 2026
Search Tags:#clustering#protein#phylogenomics#pangenome#orthogroups#presence-absence#paralogs
One-click install
npx skills add https://github.com/fmschulz/omics-skills --skill bio-protein-clustering-pangenome
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bio-protein-clustering-pangenome
Source: https://github.com/fmschulz/omics-skills/tree/main/skills/bio-protein-clustering-pangenome
Command: npx skills add https://github.com/fmschulz/omics-skills --skill bio-protein-clustering-pangenome

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Cluster proteins into orthogroups and derive pan-genome matrices to support presence/absence analyses across many genomes.

Core Features & Use Cases

  • Orthogroup clustering with MMseqs2/ProteinOrtho to generate consistent gene families across genomes.
  • Pangenome statistics including core, accessory, cloud, and singleton partitions, plus single-copy orthologs for phylogenomics.
  • Use cases include large-scale bacterial pan-genome analysis, phylogenomic prep, and comparative genomics across numerous species.

Quick Start

Cluster proteins.faa into orthogroups using MMseqs2 or ProteinOrtho and generate a presence/absence matrix with core, accessory, and singleton classifications.

Frequently Asked Questions about bio-protein-clustering-pangenome

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I cluster proteins into orthogroups for a pangenome analysis?▼

Pangenome matrices map the presence and absence of orthogroups across multiple genomes, allowing you to identify core, accessory, cloud, and singleton gene partitions for comparative genomics.

Can I use MMseqs2 or OrthoFinder to generate a presence-absence matrix?▼

Yes, you can use MMseqs2, ProteinOrtho, or OrthoFinder to cluster protein FASTA inputs, which then generates orthogroup tables and presence/absence matrices for downstream phylogenomic preparation.

Does this pangenome clustering workflow support eukaryotic genomes?▼

Yes, this pangenome clustering workflow is applicable to both large-scale prokaryotic and eukaryotic pan-genome analyses, processing protein FASTA inputs to identify core, accessory, and single-copy orthologs.

How do I identify single-copy orthologs for phylogenomic preparation?▼

You identify single-copy orthologs for phylogenomic preparation by clustering proteins into orthogroups and generating pangenome statistics that classify core, accessory, and single-copy gene partitions.

What input format is required to generate pangenome statistics and orthogroups?▼

The required input format is a protein FASTA file like proteins.faa, which clustering backends process to output orthogroup tables, presence/absence matrices, and QC reports for pangenome analysis.

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