agentsclimarketplace

Bio phylogenomics

Skill BioTender-max/awesome-bio-agent-skills/skills/omics/bio-phylogenomics

Build marker gene alignments and phylogenetic trees.From its SKILL.md

Install
npx -y skills add BioTender-max/awesome-bio-agent-skills --skill bio-phylogenomics

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.

SKILL.md

4.6 KB, ~1.0k tokens by cl100k_base, as published. Nobody here has run it

Bio Phylogenomics

Build marker gene alignments and phylogenetic trees.

Instructions

  1. Extract marker genes or SSU rRNA sequences.
  2. Align with MAFFT v7.5+ and trim with trimAl v1.4 (or ClipKIT when phylogenetically-informed trimming is preferred).
  3. Build ML trees with support values. Choose by objective first, then leaf count:
    • Exploratory placement, benchmark iterations, reference-set screening, or any time-bounded analysis: use VeryFastTree v4.0 first, even below ~2,000 taxa. Prefer VeryFastTree -boot 1000 -threads <n> < alignment.faa > tree.nw for proteins and add -nt for nucleotide alignments.
    • Final or publication-quality trees up to ~2,000 taxa: IQ-TREE v3 (v3.1.2+) for comprehensive model selection, MAST/GTRpmix, UFBoot/SH-aLRT, and defensible final inference.
    • Above ~2,000 taxa, or when memory/runtime is uncertain: VeryFastTree v4.0 (multi-threaded, SIMD, -disk-computing for very large trees).
    • Use iqtree3 -fast only when VeryFastTree is unavailable or a project explicitly requires IQ-TREE-compatible exploratory output; record that fallback in the report.
  4. Post-process trees with ETE v4 (ete4):
    • Compute tree statistics (branch lengths, distances, topology metrics).
    • Root, prune, or collapse nodes as needed.
    • Filter by bootstrap support.
    • Add taxonomic or trait annotations.
    • Generate publication-quality visualizations.
  5. Use the literature-derived analysis playbook to choose markers, reference sampling, rooting, and placement strategy appropriate for the inferred group.
  6. Identify nearest neighbors and closest named relatives for each query sequence/genome when the chosen marker/reference set supports that interpretation.
  7. Export a closest-relatives table with support values, distances, taxonomy, reference accessions, and uncertainty notes.
  8. Fetch and persist the close-relative genomes and proteomes that downstream comparative analyses will use. Save under results/bio-phylogenomics/relatives/{accession}/genome.fna and proteins.faa, plus relatives_manifest.tsv recording accession, source DB, taxonomy, genome size, gene count, and the reason for inclusion. If a relative cannot be downloaded, record the failure explicitly. Without this artifact, the comparative axes downstream cannot run.
  9. Use well-supported relatives or a documented broader comparison set to guide downstream comparative analysis with /bio-protein-clustering-pangenome and /bio-annotation.

Quick Reference

TaskAction
Run workflowFollow the steps in this skill and capture outputs.
Validate inputsConfirm required inputs and reference data exist.
Review outputsInspect reports and QC gates before proceeding.
Tool docsSee docs/README.md.

Input Requirements

Prerequisites:

  • Tools available in the active environment (Pixi/conda/system). See docs/README.md for expected tools.
  • Marker gene set or alignments available. Inputs:
  • markers.faa (marker genes) or alignments.fasta

Output

  • results/bio-phylogenomics/alignments/
  • results/bio-phylogenomics/trees/
  • results/bio-phylogenomics/closest_relatives.tsv
  • results/bio-phylogenomics/relatives/{accession}/genome.fna
  • results/bio-phylogenomics/relatives/{accession}/proteins.faa
  • results/bio-phylogenomics/relatives_manifest.tsv
  • results/bio-phylogenomics/phylo_report.md
  • results/bio-phylogenomics/logs/

Quality Gates

  • Alignment length and missingness meet project thresholds.
  • Bootstrap support summary meets project thresholds.
  • On failure: retry with alternative parameters; if still failing, record in report and exit non-zero.
  • Verify markers.faa is non-empty and aligned sequences are consistent.
  • Marker and reference choices are justified against the literature-derived analysis playbook.
  • Closest relatives are reported with support/distance metrics or uncertainty is stated.
  • Tree interpretation distinguishes well-supported nearest relatives from weakly supported placements.
  • relatives_manifest.tsv is populated and the matching genome/proteome files are present on disk (or each failure is recorded with a reason).

Examples

Example 1: Expected input layout

markers.faa (marker genes) or alignments.fasta

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.

What ships with it: 8 files

42.3 KB alongside SKILL.md

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.