Ortholog Inference

What the source does

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Five audit layers

Gates applied: no behavioural pass.

Audit 0.4.1 · source sha c8c1fc3a2b13 · 19 Oct 2026Report an issue or request a re-scan

• PublisherGPTomics GitHub organizationOwner of the repository this skill is read from
• Source folderGPTomics/bioSkills/comparative-genomics/ortholog-inferenceThe exact folder we audited
• LicenceMITAs the repository states it
• Commit pinned for this verdictc8c1fc3a2b13A new audit runs when the source changes
• Repository statusArchivedLast push 65 days ago
• Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

Its description: Infer orthologous genes and gene families across species using OrthoFinder3 (HOG-based phylogenetic orthology), SonicParanoid2, Broccoli, ProteinOrtho, OMA / FastOMA hierarchical orthologous groups, eggNOG-mapper,…

---
name: bio-comparative-genomics-ortholog-inference
description: Infer orthologous genes and gene families across species using OrthoFinder3 (HOG-based phylogenetic orthology), SonicParanoid2, Broccoli, ProteinOrtho, OMA / FastOMA hierarchical orthologous groups, eggNOG-mapper, JustOrthologs, and TOGA whole-genome-alignment orthology. Use when building single-copy ortholog sets for phylogenomics, classifying co-orthologs and in/out-paralogs after gene duplication, propagating functional annotation via orthology with awareness of the ortholog conjecture, distinguishing speciation from duplication via gene-tree species-tree reconciliation, computing Quest-for-Orthologs benchmark performance, or running synteny-aware ortholog detection in WGD-affected lineages.
tool_type: mixed
primary_tool: OrthoFinder
---

## Version Compatibility

Reference examples tested with: OrthoFinder 3.0+ (Emms et al 2026 Nat Methods 23:1327), SonicParanoid 2.0.8+ (Cosentino 2024), Broccoli 1.2+ (Derelle 2020), ProteinOrtho 6.3.0+ (Lechner 2011 + recent), OMA standalone 2.6.0+, FastOMA 0.3.5+ (Majidian 2025), eggNOG-mapper 2.1.12+, JustOrthologs 2.0+, DIAMOND 2.1.10+, MMseqs2 17-b804f+, IQ-TREE 2.3.6+, BUSCO 5.7+, Compleasm 0.2.7+, BioPython 1.84+, R 4.4+ for downstream tree-based reconciliation.

Before using code patterns, verify installed versions match. If versions differ:
- CLI: `orthofinder --help`; `sonicparanoid --help`; `oma --help`
- Python: `pip show eggnog-mapper`; `which fastoma`

If code throws `Diamond requires N more sequences than provided`, `KeyError on species tree taxa`, `STAG branch length 0`, or `HOG file format mismatch`, the OrthoFinder v2 -> v3 file layout changed (Orthogroups/ -> Phylogenetic_Hierarchical_Orthogroups/; rooted gene trees are now per-HOG); update parsing accordingly.

# Ortholog Inference

**"Find the orthologs of my gene(s) across these species"** -> Choose between graph-based (RBH / similarity-clustering: fast, lower recall) and tree-based (gene-tree reconciliation: higher accuracy, slower) frameworks; recognize that "orthology" splits into 1:1, 1:many, many:many, and the practical unit for most pipelines is the **HOG (Hierarchical Orthologous Group)** -- a maximal cluster of genes descended from a single ancestral gene at a defined taxonomic level (Altenhoff 2013 PLoS ONE 8:e53786). The "ortholog conjecture" (orthologs more functionally similar than paralogs) is supported but weakly (Altenhoff 2012 PLoS Comp Biol 8:e1002514); don't treat 1:1 ortholog labeling as automatic functional equivalence.

- CLI: `orthofinder -f proteomes/ -t 16 -M msa` -- HOG output in v3 layout
- CLI: `sonicparanoid -i proteomes/ -o output --mode default` -- ML predictor + protein language model
- CLI: `broccoli.py -dir proteomes/ -threads 16` -- direct OG with chimeric handling
- CLI: `oma standalone` HOG inference at every taxonomic level
- CLI: `proteinortho6.pl --project=run proteomes/*.faa` -- graph clustering with optional synteny
- CLI: `emapper.py -i proteins.faa --output project --cpu 16` -- eggNOG annotation transfer

## Algorithmic Taxonomy

| Tool | Approach | Output | Strength | Fails when |
|------|----------|--------|----------|------------|
| OrthoFinder3 (Emms et al 2026 Nat Methods) | DIAMOND2-ultra search -> gene trees -> rooted via STRIDE -> HOG inference at every node | HOGs at every taxonomic level, orthologs, species tree, gene-duplication events | Best Quest-for-Orthologs benchmark (Altenhoff 2024); HOGs are ~7% more accurate than v2 orthogroups (5-7% higher f-score); outgroup inclusion further improves accuracy | Slow with > 200 species without `-c 1` clustering pre-step; new file layout breaks old parsers |
| SonicParanoid2 (Cosentino 2024 GB 25:195) | RBH + ML classifier with protein language model embeddings | Pairwise orthologs + orthogroups | Best accuracy among graph methods at competitive speed; ML correction reduces InParanoid errors | InParanoid lineage still has paralogy confusion in WGD clades; close-relative duplications hard to resolve |
| Broccoli (Derelle 2020 MBE 37:3389) | k-mer similarity -> directed graph -> chimera-aware OG inference | OGs + chimera flagging | Robust to chimeric assemblies; runs without species tree | Less accurate than OrthoFinder on benchmark; no HOG output |
| ProteinOrtho 6 (Lechner 2011 BMC Bioinf 12:124) | Pairwise BLAST/DIAMOND + connectivity graph; optional synteny module | Orthogroups + synteny option | Fast; scales to 1000+ genomes; `-synteny` enables co-linear-anchor filtering | Lower recall than tree-based; synteny module slow and requires GFFs |
| OMA standalone (Altenhoff 2019 GR 29:1152) | Strict RBH + verification + HOG inference | HOG database; orthologs at each taxonomic level | Conservative; highest precision in QfO benchmarks; "Fast" mode for prefiltering | Lowest recall among methods (Altenhoff 2024); slow for large datasets |
| FastOMA (Majidian 2025 Nat Methods 22:269) | OMA HOG inference with GPU-accelerated DIAMOND + Roothap | Same HOG output as OMA, 10-100x faster | Scales OMA to 1000+ genomes | Newer; less benchmarked in production |
| eggNOG-mapper 2 (Cantalapiedra 2021 MBE 38:5825) | DIAMOND/MMseqs2 against eggNOG 5 -> map to precomputed orthogroups | OGs + functional annotation (GO/KEGG/COG) | Standard for functional annotation propagation; phylogeny-aware | Pre-computed OGs; cannot add novel species coherently; only as fresh as eggNOG release |
| JustOrthologs (Miller 2019 Bioinformatics 35:546) | DNA-based; exon-aware; close-species RBH | Pairwise orthologs | Extremely fast for closely related species (same family); preserves splice variants | Only suitable for closely related species |
| TOGA (Kirilenko 2023 Science 380:eabn3107) | Whole-genome-alignment chain -> ML projection + intactness classification | Per-query orthologs with intact/lost/missing call | Modern paradigm for vertebrate-scale orthology; handles gene loss explicitly; integrates with CESAR 2.0 | Requires WGA (Cactus); not designed for

Excerpt, first 6,000 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

git clone https://github.com/rderelle/Broccoli && cd Broccoli && pip install .
pip install fastoma
git clone https://github.com/ridgelab/justOrthologs && cd justOrthologs && python setup.py install
git clone https://github.com/ridgelab/justOrthologs

git clone https://github.com/GPTomics/bioSkills
git -C bioSkills checkout c8c1fc3a2b13

Works in

1. 2026-10-19
   ✓SAFE B 89 / 100

   first audit · source c8c1fc3a2b13

Questions about Ortholog Inference

• github.com/GPTomics/bioSkills/tree/main/comparative-genomics/ort — the audited source at commit c8c1fc3a2b13 and every finding aboveObserved · 19 Oct 2026

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