Phylogenetic Tree Styler

Features

Beautify phylogenetic trees, add taxonomy color blocks, Bootstrap values, and timelines.

Usage

python3 scripts/main.py --input <input_tree.nwk> --output <output.png> [options]

Parameters

Parameter	Description	Default
-i, --input	Input Newick format phylogenetic tree file	Required
-o, --output	Output image file path	tree_styled.png
-f, --format	Output format: png, pdf, svg	png
-w, --width	Image width (pixels)	1200
-h, --height	Image height (pixels)	800
--show-bootstrap	Show Bootstrap values	False
--bootstrap-threshold	Only show Bootstrap values above this threshold	50
--taxonomy-file	Species taxonomy information file (CSV format: name,domain,phylum,class,order,family,genus)	None
--show-timeline	Show timeline	False
--root-age	Root node age (million years ago)	None
--branch-color	Branch color	black
--leaf-color	Leaf node label color	black

Examples

Basic Beautification

python3 scripts/main.py -i tree.nwk -o tree_basic.png

Show Bootstrap Values

python3 scripts/main.py -i tree.nwk -o tree_bootstrap.png --show-bootstrap --bootstrap-threshold 70

Add Taxonomy Color Blocks

python3 scripts/main.py -i tree.nwk -o tree_taxonomy.png --taxonomy-file taxonomy.csv

Add Timeline

python3 scripts/main.py -i tree.nwk -o tree_timeline.png --show-timeline --root-age 500

Comprehensive Usage

python3 scripts/main.py -i tree.nwk -o tree_full.png \
    --show-bootstrap --bootstrap-threshold 70 \
    --taxonomy-file taxonomy.csv \
    --show-timeline --root-age 500

Taxonomy Information File Format

taxonomy.csv example:

name,domain,phylum,class
Species_A,Bacteria,Proteobacteria,Gammaproteobacteria
Species_B,Bacteria,Firmicutes,Bacilli
Species_C,Archaea,Euryarchaeota,Methanobacteria

Dependencies

• Python 3.8+
• ete3
• matplotlib
• numpy
• pandas

Install dependencies:

pip install ete3 matplotlib numpy pandas

Input Format

Supports standard Newick format (.nwk or .newick):

((A:0.1,B:0.2)95:0.3,(C:0.4,D:0.5)88:0.6);

Bootstrap values can be placed at node label positions (like the 95, 88 above).

Risk Assessment

Risk Indicator	Assessment	Level
Code Execution	Python/R scripts executed locally	Medium
Network Access	No external API calls	Low
File System Access	Read input files, write output files	Medium
Instruction Tampering	Standard prompt guidelines	Low
Data Exposure	Output files saved to workspace	Low

Security Checklist

• No hardcoded credentials or API keys
• No unauthorized file system access (../)
• Output does not expose sensitive information
• Prompt injection protections in place
• Input file paths validated (no ../ traversal)
• Output directory restricted to workspace
• Script execution in sandboxed environment
• Error messages sanitized (no stack traces exposed)
• Dependencies audited

Prerequisites

No additional Python packages required.

Evaluation Criteria

Success Metrics

• Successfully executes main functionality
• Output meets quality standards
• Handles edge cases gracefully
• Performance is acceptable

Test Cases

1. Basic Functionality: Standard input → Expected output
2. Edge Case: Invalid input → Graceful error handling
3. Performance: Large dataset → Acceptable processing time

Lifecycle Status

• Current Stage: Draft
• Next Review Date: 2026-03-06
• Known Issues: None
• Planned Improvements:
  • Performance optimization
  • Additional feature support