Comparative Genomics

SkillAI & models

Workflow for orthology, synteny, ancestral reconstruction, and evolutionary comparison across genomes.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Comparative Genomics skill

What this skill tells your AI

The instructions your AI receives, as published by biotender-max/awesome-bio-agent-skills in skills/bioclaw_hub/comparative-genomics/SKILL.md and read by ahel’s review.

Version Compatibility

Reference examples assume recent stable releases of the preferred tools, especially orthology and the other tools listed below.

Before using code or command patterns, verify installed versions match the environment:

  • Python: python -c "import <module>; print(<module>.__version__)"
  • CLI: <tool> --version
  • If signatures differ, inspect the installed help or API and adapt the pattern instead of retrying unchanged.

Overview

Workflow for orthology, synteny, ancestral reconstruction, and evolutionary comparison across genomes.

When To Use This Skill

  • use when the task is cross-genome comparison or evolutionary inference
  • use when assembled genomes and annotations are available for multiple taxa or strains
  • use when the user needs orthologs, synteny blocks, or positive-selection style summaries

Quick Route

  • If the input is raw or minimally processed data, start with validation and QC before any modeling.
  • If the input is already processed, skip directly to the first workflow step that matches the user goal.
  • If the user asks for a biological conclusion, always produce at least one QC or confidence artifact alongside the final result.

Progressive Disclosure

  • Read references/technical_reference.md when you need deeper tool-selection rules, environment adaptation notes, or extra validation guidance.
  • Keep SKILL.md as the main execution path and load the reference file only when the task or failure mode needs the extra detail.

Default Rules

  • Prefer Python-first workflows unless the task explicitly requires something else.
  • Keep intermediate and final outputs separated.
  • Record software versions, reference builds, and key parameters when they affect interpretation.
  • Favor reproducible tables and figures over one-off interactive-only outputs.

Expected Inputs

  • assemblies
  • gene annotations
  • optional phylogenetic context

Expected Outputs

  • ortholog tables
  • synteny outputs
  • evolutionary comparison summaries

Preferred Tools

  • orthology tools
  • alignment and phylogeny utilities
  • pandas

Starter Pattern

Preferred starting point: orthology
Inputs: assemblies, gene annotations, optional phylogenetic context
Outputs: ortholog tables, synteny outputs, evolutionary comparison summaries

Workflow

1. Define comparison scale

Clarify whether the task is gene-level, synteny-level, or phylogenomic.

2. Standardize annotations

Use consistent naming, feature models, and assemblies before comparing genomes.

3. Infer shared and divergent elements

Run orthology, synteny, or evolutionary analyses appropriate to the question.

4. Interpret in biological context

Separate technical annotation differences from genuine biological divergence.

5. Export concise comparison artifacts

Save tables and figures that highlight conserved versus lineage-specific patterns.

Output Artifacts

  • Recommended output layout:
    • results/ for final tables and serialized objects
    • figures/ for plots and static visual exports
    • qc/ for checks that justify downstream interpretation
  • Minimum expected outputs for this skill:
  • ortholog tables
  • synteny outputs
  • evolutionary comparison summaries

Quality Review

  • Confirm identifiers and metadata join correctly before modeling or summarizing.
  • Generate at least one QC artifact before final biological interpretation.
  • Keep raw or minimally processed inputs separate from transformed outputs.
  • Record reference build, caller assumptions, and filtering rules in the final outputs.
  • Separate raw calls from filtered or interpreted results.

Anti-Patterns

  • comparing genomes with incompatible annotation quality without caveats
  • overstating adaptive evolution from weak evidence
  • mixing orthology and homology claims carelessly

Related Skills

  • Variant Calling
  • Copy Number
  • Long-Read Genomics
  • Genome Assembly

Optional Supplements

  • None required for the first pass.

Signals

GitHub stars
178
Forks
32
Last commit
Jul 2026
Advanced
Catalog kind
skill
Gateway key
comparative-genomics
Source
github.com/biotender-max/awesome-bio-agent-skills