Agent skill

bio-epidemiological-genomics-phylodynamics

Construct time-scaled phylogenies and infer evolutionary dynamics using TreeTime and BEAST2 for outbreak analysis. Estimate divergence times, molecular clock rates, and ancestral states. Use when dating outbreak origins, estimating transmission rates, or building time-calibrated trees.

FreedomIntelligencegithub.com/FreedomIntelligenceGitHub ↗
claude-codeships scripts
Install
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-epidemiological-genomics-phylodynamics --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 3
SKILL.md size: 7 KB
Bundled scripts: yes
Path: skills/bio-epidemiological-genomics-phylodynamics/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 2,909
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

## Version Compatibility Reference examples tested with: BioPython 1.83+, TreeTime 0.11+, scanpy 1.10+ Before using code patterns, verify installed versions match. If versions differ: - Python: `pip show <package>` then `help(module.function)` to check signatures - CLI: `<tool> --version` then `<tool> --help` to confirm flags If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # Phylodynamics **"Build a time-scaled tree for my outbreak"** → Estimate divergence times and molecular clock rates from dated sequences to reconstruct outbreak timing and evolutionary dynamics. - Python: `treetime.TreeTime()` for maximum likelihood time-scaled trees - CLI: `treetime --tree tree.nwk --aln aln.fasta --dates dates.tsv` ## TreeTime Basic Usage ```python from treetime import TreeTime from Bio import Phylo # Load tree and alignment tree = Phylo.read('tree.nwk', 'newick') # Create TreeTime object with dates # dates_file: tab-separated with columns 'name' and 'date' # Date formats: 2020.5, 2020-06-15, numeric (decimal year) tt = TreeTime( tree=tree, aln='alignment.fasta', dates='dates.tsv', gt

What's inside
Steps it walks through
  1. Version Compatibility
  2. TreeTime Basic Usage
  3. TreeTime CLI
  4. Date File Format
  5. Interpret Clock Results
  6. Skyline Plot (Population Dynamics)
  7. BEAST2 Integration
  8. Related Skills
Ships with 2 files
  • examples/treetime_analysis.py
  • usage-guide.md
Commands it runs
Install treetime
pip install phylo-treetime
Basic time tree
treetime --tree tree.nwk --aln alignment.fasta --dates dates.tsv --outdir results/
With coalescent prior (for population dynamics)
treetime --tree tree.nwk --aln alignment.fasta --dates dates.tsv \
Ancestral sequence reconstruction
treetime ancestral --tree tree.nwk --aln alignment.fasta --outdir results/
Mugration (discrete trait analysis, e.g., geographic spread)
treetime mugration --tree tree.nwk --states locations.tsv \
More from OpenClaw-Medical-Skills
All skills →
About this skill
What does the bio-epidemiological-genomics-phylodynamics skill do?

Construct time-scaled phylogenies and infer evolutionary dynamics using TreeTime and BEAST2 for outbreak analysis. Estimate divergence times, molecular clock rates, and ancestral states. Use when dating outbreak origins, estimating transmission rates, or building time-calibrated trees.

How do I install it?

Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-epidemiological-genomics-phylodynamics --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From FreedomIntelligence/OpenClaw-Medical-Skills, a repository with 2,909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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