Pathogen Epidemiological Genomics

SkillAI & models

Workflow for outbreak-style pathogen genomics, surveillance, lineage assignment, and transmission-oriented comparative analysis.

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 Pathogen Epidemiological 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/pathogen-epi-genomics/SKILL.md and read by ahel’s review.

Version Compatibility

Reference examples assume recent stable releases of the preferred tools, especially phylogenetics 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 outbreak-style pathogen genomics, surveillance, lineage assignment, and transmission-oriented comparative analysis.

When To Use This Skill

  • use when the task is pathogen surveillance, lineage assignment, or outbreak genomics
  • use when sample metadata include time, geography, or host context
  • use when genomic comparison must be linked to epidemiological interpretation

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

  • pathogen genomes or read sets
  • collection metadata
  • reference resources

Expected Outputs

  • lineage assignments
  • cluster or outbreak summaries
  • surveillance-ready tables or figures

Preferred Tools

  • phylogenetics utilities
  • variant and lineage-calling tools
  • pandas

Starter Pattern

Preferred starting point: phylogenetics
Inputs: pathogen genomes or read sets, collection metadata, reference resources
Outputs: lineage assignments, cluster or outbreak summaries, surveillance-ready tables or figures

Workflow

1. Standardize metadata

Ensure time, location, and sample identifiers are consistent before analysis.

2. Generate comparable genomic summaries

Call variants or consensus sequences in a way that supports cross-sample comparison.

3. Assign lineages or clusters

Use pathogen-appropriate nomenclature and clustering logic.

4. Link genomics to epidemiology

Summarize genomic findings with explicit metadata context and caution around transmission claims.

5. Export surveillance outputs

Save lineage tables, phylogenies, and cluster summaries.

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:
  • lineage assignments
  • cluster or outbreak summaries
  • surveillance-ready tables or figures

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.
  • Review sample contamination, depth differences, and database choice before comparing communities.
  • State clearly whether outputs are relative abundance, counts, or derived functions.

Anti-Patterns

  • claiming direct transmission from genomics alone
  • mixing consensus builds or lineage schemes without stating it
  • ignoring metadata QC in outbreak analyses

Related Skills

  • Metagenomics
  • Microbiome Amplicon
  • Phylogenetics

Optional Supplements

  • phylogenetics

Signals

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