Skip to content
cccskills
FreePublished on GitHub

biopython-phylo

Use Bio.Phylo to read/write phylogenetic trees and perform visualization and statistics; use when tree parsing/conversion, pruning/rerooting, distance calculation, or plotting is required.

The English summary is being prepared. Showing the original description.

See how to install

Files included (4)

  • SKILL.md6.8 KB
  • biopython-phylo_audit_result_v1.json12.0 KB
  • config/task_config.json2 B
  • references/phylogenetics.md14.1 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Source: https://github.com/aipoch/medical-research-skills

biopython-phylo

When to Use

  • Converting phylogenetic tree files between Newick, NEXUS, and phyloXML formats.
  • Traversing a tree to locate clades, prune taxa, or reroot at a specific node/outgroup.
  • Computing pairwise distances, distance matrices, or basic tree statistics (e.g., branch length summaries).
  • Producing quick tree visualizations as ASCII output for logs/CLI workflows.
  • Generating publication-ready plots of trees using Matplotlib.

Key Features

  • Read and write phylogenetic trees via Bio.Phylo with support for common formats (Newick/NEXUS/phyloXML).
  • Tree manipulation utilities: traversal, clade selection, pruning, and rerooting.
  • Distance computation and simple statistics derived from branch lengths/topology.
  • Visualization options:
    • ASCII rendering for terminal output.
    • Matplotlib-based plotting for figures.

Dependencies

  • biopython>=1.80
  • Optional (for plotting):
    • matplotlib>=3.7

Example Usage

The following example is runnable end-to-end and follows the conventions:

  • Configuration is stored in config/task_config.json.
  • Script is invoked as python scripts/phylo_task.py.
  • All file I/O uses encoding="utf-8".
  • JSON output uses ensure_ascii=False.

config/task_config.json

{
  "input_tree": "data/input_tree.nwk",
  "input_format": "newick",
  "output_tree": "artifacts/output_tree.xml",
  "output_format": "phyloxml",
  "prune_terminals": ["TaxonC"],
  "reroot_outgroup": "TaxonB",
  "ascii_out": "artifacts/tree_ascii.txt",
  "stats_out": "artifacts/tree_stats.json",
  "plot_enabled": true,
  "plot_out": "artifacts/tree_plot.png"
}

scripts/phylo_task.py

import json
import os
from typing import Any, Dict, List, Optional

from Bio import Phylo


def ensure_parent_dir(path: str) -> None:
    parent = os.path.dirname(path)
    if parent:
        os.makedirs(parent, exist_ok=True)


def load_config(path: str) -> Dict[str, Any]:
    with open(path, "r", encoding="utf-8") as f:
        return json.load(f)


def prune_by_names(tree, names: List[str]) -> None:
    # Prune terminals by name if present
    for n in names:
        if tree.find_any(name=n) is not None:
            tree.prune(target=n)


def reroot_by_outgroup_name(tree, outgroup_name: str) -> None:
    outgroup = tree.find_any(name=outgroup_name)
    if outgroup is None:
        raise ValueError(f"Outgroup '{outgroup_name}' not found in tree terminals/clades.")
    tree.root_with_outgroup(outgroup)


def tree_stats(tree) -> Dict[str, Any]:
    terminals = tree.get_terminals()
    nonterminals = tree.get_nonterminals()

    # Collect branch lengths (may include None)
    lengths = []
    for clade in tree.find_clades(order="preorder"):
        if clade.branch_length is not None:
            lengths.append(float(clade.branch_length))

    return {
        "n_terminals": len(terminals),
        "n_nonterminals": len(nonterminals),
        "n_clades_total": len(terminals) + len(nonterminals),
        "branch_length_count": len(lengths),
        "branch_length_sum": sum(lengths) if lengths else 0.0,
        "branch_length_min": min(lengths) if lengths else None,
        "branch_length_max": max(lengths) if lengths else None,
        "branch_length_mean": (sum(lengths) / len(lengths)) if lengths else None,
    }


def write_ascii(tree, out_path: str) -> None:
    ensure_parent_dir(out_path)
    with open(out_path, "w", encoding="utf-8") as f:
        Phylo.draw_ascii(tree, file=f)


def plot_tree(tree, out_path: str) -> None:
    # Optional dependency: matplotlib
    import matplotlib
    matplotlib.use("Agg")  # headless backend
    import matplotlib.pyplot as plt

    ensure_parent_dir(out_path)
    fig = plt.figure(figsize=(10, 6))
    ax = fig.add_subplot(1, 1, 1)
    Phylo.draw(tree, do_show=False, axes=ax)
    fig.tight_layout()
    fig.savefig(out_path, dpi=200)
    plt.close(fig)


def main(config_path: str = "config/task_config.json") -> None:
    cfg = load_config(config_path)

    input_tree = cfg["input_tree"]
    input_format = cfg.get("input_format", "newick")
    output_tree = cfg["output_tree"]
    output_format = cfg.get("output_format", "phyloxml")

    prune_terminals: List[str] = cfg.get("prune_terminals", [])
    reroot_outgroup: Optional[str] = cfg.get("reroot_outgroup")

    ascii_out = cfg.get("ascii_out", "artifacts/tree_ascii.txt")
    stats_out = cfg.get("stats_out", "artifacts/tree_stats.json")

    plot_enabled = bool(cfg.get("plot_enabled", False))
    plot_out = cfg.get("plot_out", "artifacts/tree_plot.png")

    # Read
    tree = Phylo.read(input_tree, input_format)

    # Manipulate
    if prune_terminals:
        prune_by_names(tree, prune_terminals)

    if reroot_outgroup:
        reroot_by_outgroup_name(tree, reroot_outgroup)

    # Write converted tree
    ensure_parent_dir(output_tree)
    Phylo.write(tree, output_tree, output_format)

    # ASCII visualization
    write_ascii(tree, ascii_out)

    # Stats
    ensure_parent_dir(stats_out)
    with open(stats_out, "w", encoding="utf-8") as f:
        json.dump(tree_stats(tree), f, ensure_ascii=False, indent=2)

    # Plot (optional)
    if plot_enabled:
        plot_tree(tree, plot_out)


if __name__ == "__main__":
    main()

Run

python scripts/phylo_task.py

Implementation Details

  • Configuration-first execution: parameters are stored in config/task_config.json as an intermediate artifact; scripts are invoked uniformly via python scripts/<task_name>.py. Avoid stacking many CLI -- arguments; prefer config files.
  • Encoding and JSON output:
    • Always open files with encoding="utf-8".
    • When writing JSON, use ensure_ascii=False to preserve non-ASCII characters.
  • Supported formats:
    • Input/output formats are passed to Phylo.read(...) and Phylo.write(...) (e.g., newick, nexus, phyloxml).
  • Pruning:
    • Pruning is performed by terminal/clade name using tree.prune(target=<name>). Names not found are skipped (or can be treated as errors depending on your policy).
  • Rerooting:
    • Rerooting uses tree.root_with_outgroup(outgroup_clade); the outgroup is located via tree.find_any(name=...).
  • Statistics:
    • Branch lengths may be missing (None); statistics should ignore missing values.
    • Basic counts can be derived from tree.get_terminals() and tree.get_nonterminals().
  • Visualization:
    • ASCII output uses Phylo.draw_ascii(tree, file=...) for deterministic CLI-friendly rendering.
    • Matplotlib plotting uses a non-interactive backend (Agg) for headless environments and saves to an image file.

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

Transform lengthy academic papers into concise, structured 250-word abstracts.

The English summary is being prepared. Showing the original description.

aipoch/medical-research-skills2KUpdated Sep 17, 2026

Precision editing tool that reduces abstract word count through intelligent compression techniques, maintaining scientific rigor while meeting strict journal and conference requirements.

The English summary is being prepared. Showing the original description.

aipoch/medical-research-skills2KUpdated Sep 17, 2026

Refines long medical academic texts into SCI-style unstructured Chinese and English abstracts; use when you need to condense drafts/reports/summaries into bilingual abstracts and generate Summary_Report.md.

The English summary is being prepared. Showing the original description.

aipoch/medical-research-skills2KUpdated Sep 17, 2026

Generates submission-ready Elsevier/SCI Highlights from manuscript text or extracted PDF/DOCX/TXT content. Use when a user needs 3-5 concise, evidence-grounded highlight bullets for a research paper, review, meta-analysis, case report, or bioinformatics manuscript.

The English summary is being prepared. Showing the original description.

aipoch/medical-research-skills2KUpdated Sep 17, 2026

Generates complete FAERS pharmacovigilance study designs for multi-drug or class-level safety comparison inside one predefined SOC or AE family using active comparators, disproportionality analysis, subgroup characterization, and reviewer-facing evidence control.

The English summary is being prepared. Showing the original description.

aipoch/medical-research-skills2KUpdated Sep 17, 2026

Analyze data with `adme-property-predictor` using a reproducible workflow, explicit validation, and structured outputs for review-ready interpretation.

The English summary is being prepared. Showing the original description.

aipoch/medical-research-skills2KUpdated Sep 17, 2026

See all skills by aipoch

Report a problem with this skill