Bio Protein Clustering Pangenome

Bio Protein Clustering Pangenome

Cluster proteins into orthogroups and derive pangenome matrices.

Instructions

1. Cluster proteins. Choose the tool by dataset size and goal:
   • Default for orthology inference up to a few hundred genomes: OrthoFinder v3 (improved accuracy and lower RAM at scale, supports MSA-based gene trees; supersedes OrthoFinder v2 and OrthoMCL workflows).
   • Very large pangenomes where OrthoFinder is too RAM-heavy: ProteinOrtho v6.1.7+ as the fast, scalable alternative.
   • Sequence clustering (not strict orthology) and similarity search backbones: MMseqs2 v15-6f452+. Enable GPU mode (mmseqs ... --gpu) on CUDA Turing+ nodes for a ~20× speedup at near-identical sensitivity.
2. Build presence/absence matrix AND an integer copy-number matrix (orthogroup × genome) covering the query AND the close relatives produced by /bio-phylogenomics.
3. Compute core/accessory/cloud/singleton partitions.
4. Identify single-copy orthologs for phylogenetic analysis.
5. Discriminate paralogs from orthologs in multi-copy gene families.
6. Calculate pangenome statistics (completeness, orthogroup occupancy).
7. When a query genome or genome set is under study, use the literature-derived analysis playbook to choose an appropriate comparison baseline: closest relatives, a broader clade, environmental references, or a negative/control set.
8. Genome-property frontier table — produce relative_genome_metrics.tsv with one row per (query + relative) and columns for genome size, contig count, N50, gene count, coding density, GC, tRNA count, rRNA count, and any group-relevant property. Add a column that places the query in the relative distribution (percentile, min/median/max, "record-class" tag) and a column citing the literature reference defining the group's known range.
9. Synteny / conserved neighborhoods — for each pair (query, relative) compute conserved gene neighborhoods (e.g., ≥2 collinear orthologs). Tool selection:
   • Pairwise / classical: MCScanX (Nature Protocols 2024 updated protocol).
   • Multi-genome at scale (>2 assemblies, up to >3 Gbp, >15% divergence): ntSynt (BMC Biology 2025, DOI: 10.1186/s12915-025-02455-w) — alignment-free minimizer-graph approach; does not detect duplications.
   • Strain-level work where duplication detection matters: SibeliaZ. Save results as conserved_neighborhoods.tsv with columns: query_block_id, relative, relative_block_id, members (ortholog IDs), intergenic_spacing_query, intergenic_spacing_relative, spacing_ratio, notes. Flag conserved gene pairs and unusual spacing/expansions.
10. Identify discovery-relevant differences defined by the playbook, including query-specific families, missing expected families, expansions/contractions, unusual sharing patterns, and high-value unknowns. Persist as family_copy_number_comparison.tsv (query vs relative-median fold change per family) — coordinated with bio-annotation's family matrix.
11. Annotate candidate orthogroups with /bio-annotation; for high-value unknowns, route representatives to /bio-structure-annotation when structure-based inference is appropriate.
12. Produce a comparison summary that separates conserved lineage features from unusual or query-specific features and states the baseline used. The summary must report ALL of: genome-property frontier, marker-category presence/copy, family expansions/contractions, synteny conservation/breakage, and ncRNA counts side-by-side with relatives.

Quick Reference

Input Requirements

Prerequisites:

• Tools available in the active environment (Pixi/conda/system). See docs/README.md for expected tools.
• Protein FASTA inputs are available. Inputs:
• proteins.faa (FASTA protein sequences)

Output

• results/bio-protein-clustering-pangenome/orthogroups.tsv
• results/bio-protein-clustering-pangenome/presence_absence.parquet
• results/bio-protein-clustering-pangenome/copy_number_matrix.parquet
• results/bio-protein-clustering-pangenome/relative_genome_metrics.tsv
• results/bio-protein-clustering-pangenome/family_copy_number_comparison.tsv
• results/bio-protein-clustering-pangenome/conserved_neighborhoods.tsv
• results/bio-protein-clustering-pangenome/closest_relative_comparison.tsv
• results/bio-protein-clustering-pangenome/query_specific_candidates.tsv
• results/bio-protein-clustering-pangenome/pangenome_report.md
• results/bio-protein-clustering-pangenome/logs/

Quality Gates

• Cluster size distributions meet project thresholds.
• Matrix completeness meets project thresholds.
• On failure: retry with alternative parameters; if still failing, record in report and exit non-zero.
• Verify proteins.faa is non-empty and amino acid encoded.
• Comparison baseline is justified from literature, phylogeny, taxonomy, or data availability.
• Query-specific, missing, expanded, and conserved orthogroups are reported separately.
• Candidate discovery orthogroups have annotation evidence or a recommended follow-up analysis.
• relative_genome_metrics.tsv places each query in the distribution of relatives and notes the literature-defined extreme of the inferred group.
• family_copy_number_comparison.tsv reports per-family fold change vs the relative median for the full annotated family set, not only top candidates.
• conserved_neighborhoods.tsv is produced and includes intergenic spacing for both query and relative sides; broken synteny, unusual spacing, and expansions are flagged.

Examples

Example 1: Expected input layout

proteins.faa (FASTA protein sequences)

Troubleshooting

Issue: Missing inputs or reference databases Solution: Verify paths and permissions before running the workflow.

Issue: Low-quality results or failed QC gates Solution: Review reports, adjust parameters, and re-run the affected step.