phylogenetics

Infer maximum-likelihood phylogenetic trees from unaligned FASTA sequences.

Updated May 24, 2026
One-click install
npx skills add https://github.com/Estrella-231/Mathematical_modeling_tongmeng --skill phylogenetics-estrella-231
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: phylogenetics
Source: https://github.com/Estrella-231/Mathematical_modeling_tongmeng/tree/main/.agents/skills/phylogenetics
Command: npx skills add https://github.com/Estrella-231/Mathematical_modeling_tongmeng --skill phylogenetics-estrella-231

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires subprocess, argparse, ete3, matplotlib, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Phylogenetics reconstructs evolutionary relationships from biological sequences by producing phylogenetic trees and summarizing their support and structure.

Core Features & Use Cases

  • Multiple sequence alignment (MAFFT): Align nucleotide or protein FASTA sequences to prepare them for downstream inference.
  • Maximum-likelihood tree inference (IQ-TREE 2 or FastTree): Infer evolutionary trees with model selection and bootstrap support for reliability.
  • Tree analysis & visualization (ETE3): Compute basic tree statistics, root trees (midpoint or outgroup), and render publication-ready graphics.

Use case: You have a set of viral or microbial sequences collected across a study and need a defensible evolutionary tree with branch support to support outbreak or lineage interpretation.

Quick Start

Run the full pipeline on your unaligned FASTA file to generate an aligned dataset, an inferred phylogenetic tree, and a PNG visualization of the rooted tree.

Frequently Asked Questions about phylogenetics

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

FAQPage Schema
How do I build a phylogenetic tree from unaligned FASTA sequences?

To build a phylogenetic tree from unaligned FASTA sequences, the pipeline first aligns sequences using MAFFT, then infers a maximum-likelihood tree with IQ-TREE 2, and finally renders a publication-ready visualization with ETE3.

What is bootstrap support in phylogenetic tree inference and when do I need it?

Bootstrap support in phylogenetic tree inference estimates branch reliability by resampling alignment columns. You need it to produce a defensible evolutionary tree with statistical support for outbreak or lineage interpretation.

Can I use FastTree instead of IQ-TREE 2 for faster maximum-likelihood tree inference?

Yes, you can use FastTree instead of IQ-TREE 2 for faster maximum-likelihood tree inference. FastTree prioritizes computational speed, whereas IQ-TREE 2 provides comprehensive model selection and bootstrap support.

Does this phylogenetics pipeline support both nucleotide and protein sequence alignment?

Yes, this phylogenetics pipeline supports both nucleotide and protein sequence alignment. MAFFT prepares the biological sequences, allowing maximum-likelihood inference and tree visualization across both dataset types.

How do I root a phylogenetic tree and visualize it for publication?

To root a phylogenetic tree and visualize it for publication, the pipeline uses ETE3 to compute tree statistics and apply midpoint or outgroup rooting, then renders the rooted tree structure into a PNG graphic.

Do I need to install MAFFT and IQ-TREE 2 separately to run this phylogenetics workflow?

Yes, you need MAFFT and IQ-TREE 2 installed separately to run this phylogenetics workflow. The pipeline requires MAFFT for sequence alignment, IQ-TREE 2 for inference, and ETE3 for rendering.