phylogenetic-tree-styler

What This Skill Does

The phylogenetic-tree-styler is an expert-level tool designed for computational biologists and researchers who need to transform raw phylogenetic data into publication-quality visualizations. The skill automates the stylization process, allowing for the consistent application of taxonomy color blocks, annotated bootstrap values, and custom node labeling. Built on a reproducible workflow, this tool ensures that every tree generation follows a strict logic—from initial data validation to final graphic rendering—making it ideal for review-ready scientific documentation.

Installation

To integrate this skill into your OpenClaw environment, execute the following command: clawhub install openclaw/skills/skills/aipoch-ai/phylogenetic-tree-styler

Ensure your local environment meets the dependency requirements: Python 3.8+ and the necessary libraries (ete3, matplotlib, numpy, and pandas). You can install these by navigating to the package directory and running pip install -r requirements.txt or manually installing the dependencies via pip install ete3 matplotlib numpy pandas.

Use Cases

• Scientific Publication: Standardize tree formatting for journals that require specific taxonomy color-coding and clear bootstrap support values.
• Large-Scale Phylogenomics: Process high-throughput datasets where manual styling in GUI software is error-prone or time-consuming.
• Reproducible Research: Create a version-controlled pipeline where tree styling settings are documented as code rather than hidden inside manual software configurations.
• Automated Reporting: Generate consistent tree diagrams as part of an automated analytical pipeline for sequence analysis projects.

Example Prompts

1. "Analyze the phylogeny file at ./data/sequences.nwk and apply the taxonomy styling defined in ./references/config.json, outputting a high-res PDF."
2. "Generate a phylogenetic tree from the provided bootstrap results, highlighting the Clade X node with a distinct color and ensuring all bootstrap values above 70 are displayed."
3. "Run a diagnostic check on the alignment file and produce a stylized tree, but if the bootstrap values fall below 50, please log these as exceptions in a summary report."

Tips & Limitations

• Configuration: Always review the CONFIG block in scripts/main.py before batch processing, as parameter assumptions directly affect visual outputs.
• Input Validation: Ensure your Newick or Nexus files are correctly formatted, as the ete3 engine is strict regarding tree structure syntax.
• Scalability: For extremely large trees (10,000+ leaves), ensure sufficient local memory, as rendering complex matplotlib figures can be resource-intensive.
• Documentation: Always store the output with the corresponding input configuration file to maintain a fully reproducible audit trail for your research.