biogeobears

Automate BioGeoBEARS biogeographic analysis on phylogenetic trees with model comparison.

12|1|Updated Oct 17, 2025
One-click install
npx skills add https://github.com/brunoasm/my_claude_skills --skill biogeobears
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: biogeobears
Source: https://github.com/brunoasm/my_claude_skills/tree/main/biogeobears
Command: npx skills add https://github.com/brunoasm/my_claude_skills --skill biogeobears

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires anthropic>=0.40.0, pybtex>=0.24.0, rispy>=0.6.0, json-repair>=0.25.0, jsonschema>=4.20.0, pandas>=2.0.0, openpyxl>=3.1.0, pyreadr>=0.5.0, requests>=2.31.0, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill automates complete phylogenetic biogeographic analyses using BioGeoBEARS in R. It handles input validation, analysis setup, model comparison, and visualizations, dramatically reducing setup time and ensuring reproducible workflows.

Core Features & Use Cases

  • Input validation and reformatting: checks phylogenetic trees and geography data, formats inputs for BioGeoBEARS.
  • Automated workflow generation: creates an organized analysis folder structure and a customized RMarkdown script that fits multiple biogeographic models (DEC, DEC+J, DIVALIKE, DIVALIKE+J, BAYAREALIKE, BAYAREALIKE+J).
  • Model comparison & visualization: compares models with AIC/AICc/AIC weights, and generates publication-ready visualizations (pie charts and text labels) of ancestral ranges.
  • Use Case: Reconstruct ancestral ranges along a phylogeny and compare biogeographic models to infer dispersal/extinction patterns.

Quick Start

Gather your tree and geography files, then run the included workflow to execute a full BioGeoBEARS analysis with automatic results generation.

Frequently Asked Questions about biogeobears

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I reconstruct ancestral geographic ranges on a phylogenetic tree?

Ancestral range reconstruction uses biogeographic models fitted to phylogenetic trees to infer where species' ancestors lived. This Skill automates the process by validating your tree and geography data, fitting six biogeographic models (DEC, DEC+J, DIVALIKE, DIVALIKE+J, BAYAREALIKE, BAYAREALIKE+J) using BioGeoBEARS in R, and generating visualizations and statistical comparisons to identify the best model.

What format should my phylogenetic tree and geography data be in?

Your phylogenetic tree must be rooted with tip labels matching your geography data. Geography data is reformatted into BioGeoBEARS-compatible PHYLIP format by this Skill. Supported input formats include Newick trees and tabular geography assignments; the Skill validates and converts them automatically during setup.

How do I compare biogeographic models to find the best fit?

Model comparison uses AIC, AICc, and AIC weights alongside likelihood ratio tests to rank competing hypotheses. This Skill fits all six standard models, calculates comparison statistics, and outputs HTML reports with parameter estimates (d, e, j values) and publication-ready visualizations showing ancestral ranges at each node.

Can I use this Skill if I'm not familiar with R or BioGeoBEARS?

Yes. This Skill generates a customized RMarkdown script and handles input validation, folder setup, and analysis execution automatically. You provide a rooted phylogenetic tree and geography data; the Skill manages the R workflow, model fitting, and result generation without requiring prior BioGeoBEARS experience.

What output does this Skill produce?

Output includes an organized analysis folder with organized scripts, HTML reports containing model comparison statistics and parameter estimates, and publication-ready visualizations (pie charts and text labels) of ancestral ranges. All results are formatted for direct inclusion in manuscripts.

What if my phylogenetic tree and geography data don't match?

The Skill validates that tree tip labels correspond to geography data entries before analysis. If mismatches exist, validation fails with diagnostic feedback. You must reconcile tip labels and geography assignments before running the analysis.