Pathogen Epidemiological Genomics
SkillAI & modelsWorkflow for outbreak-style pathogen genomics, surveillance, lineage assignment, and transmission-oriented comparative analysis.
Available today. Use it from your connected AI after setup.
No other account needed.
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.mdwhen you need deeper tool-selection rules, environment adaptation notes, or extra validation guidance. - Keep
SKILL.mdas 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 objectsfigures/for plots and static visual exportsqc/for checks that justify downstream interpretation
- Minimum expected outputs for this skill:
lineage assignmentscluster or outbreak summariessurveillance-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
MetagenomicsMicrobiome AmpliconPhylogenetics
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