bio-comparative-genomics-ortholog-inference

What this skill does

## Version Compatibility

Reference examples tested with: OrthoFinder 3.0+ (bioRxiv 2025.07.15.664860), SonicParanoid 2.0.8+ (Cosentino 2023), 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 Comp Biol 9:e1002954). 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 & Kelly 2025 bioRxiv) | 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 12% more accurate than v2 orthogroups, 20% with outgroup | Slow with > 200 species without `-c 1` clustering pre-step; new file layout breaks old parsers |
| SonicParanoid2 (Cosentino 2023 NAR 51:e85) | 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 NAR 47:D424) | 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 NAR 53:D421) | 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 2 (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 prokaryotes or fungi |
| HOGENOM / HOGsuite (Penel 2009 BMC Bioinf 10:S3) | Tree-based HOGs in databases | Pre-computed HOG database | Legacy; for downstream use of stored HOGs | Not for new computation; outdated taxon sampling |

Methodology evolves; Quest-for-Orthologs benchmarks (Altenhoff 2024 Genome Biol 25:115) refresh annually. Verify the current QfO benchmark results before locking on a single tool for novel benchmarking-grade work.

## Decision Tree by Experimental Scenario

| Scenario | Recommended approach | Why |
|----------|------------------------|-----|
| 5-50 vertebrate / animal genomes for phylogenomics | OrthoFinder3 `-M msa -A mafft -T iqtree` | HOG quality at moderate scale; species tree included |
| 50-200 genomes, any clade | OrthoFinder3 default; SonicParanoid2 as second method | Cross-validate consensus HOGs |
| 200-1000 genomes, scaling required | FastOMA or SonicParanoid2 | OrthoFinder3 slow; cluster-first option (`-c 1`) helps |
| 1000+ bacterial genomes (pangenome scope) | Use [[pangenome-analysis]] pipeline; OrthoFinder unsuitable | Pangenome-specific tools needed |
| Closely related strains / same family | JustOrthologs or ProteinOrtho with synteny | Fast; preserves splice variants |
| WGD-affected lineage (plants, salmonids, teleosts) | OrthoFinder3 + synteny verification (see [[synteny-analysis]]); or GENESPACE | WGD inflates paralogy; synteny anchoring required |
| Functional annotation transfer | eggNOG-mapper 2 | Pre-computed; phylogeny-aware; integrates GO/KEGG |
| Single-copy orthologs for concatenation phylogenomics | OrthoFinder3 `Phylogenetic_Hierarchical_Orthogroups/N0.tsv` filter for 1:1 | Most rigorous HOG layer; standard concatenation input |
| Gene-loss detection across mammals/birds at scale | TOGA + CESAR 2.0 | Explicit intact/lost classification; handles assembly-gap noise |
| Functional annotation transfer in poorly characterized genome | eggNOG-mapper + OrthoFinder3 single-copy orthologs cross-validated | Functional priors + phylogenetic confidence |
| Ortholog detection in highly fragmented assembly | BUSCO/Compleasm first to assess completeness; flag affected OGs | Assembly fragmentation creates false absence -> spurious lineage-specific losses |
| Distant homolog detection (50-200 Myr divergence) | MMseqs2 sensitive (`-s 7.5`) + OrthoFinder3 | Default DIAMOND misses distant homologs; sensitive search needed |
| Phylogenetic orthology with paralog-tolerant species trees | ASTRAL-Pro2 on OrthoFinder gene trees | Coalescent species tree from gene trees; handles paralogy explicitly |
| HOG-level functional propagation across many species | OMA standalone HOG database | Strict hierarchical orthology; supports functional propagation per taxonomic level |
| Synteny-anchored orthology in repeat-heavy genome | ProteinOrtho `-synteny` or GENESPACE | Filters tandem duplicates; use