phylogenetics

Phylogenetics - Phylogenetic Analysis and Tree Construction

Skill Overview

The Phylogenetics skill provides a complete phylogenetic analysis workflow—from multiple sequence alignment (MAFFT) to maximum-likelihood tree building (IQ-TREE 2, FastTree), and then to phylogenetic tree visualization (ETE3). It helps you reconstruct the evolutionary history of biological sequences.

Use Cases

1. Viral Phylogenetic Tracking and Outbreak Source Tracing

Used to track viral transmission routes and estimate transmission times, for example, analyzing the evolutionary relationships among SARS-CoV-2 variants and reconstructing transmission chains. Molecular clock analysis is used to estimate divergence times, providing a basis for public health decisions.

2. Microbial Genomics and Species Evolution Analysis

Build microbial species phylogenetic trees based on 16S rRNA or core genomes to support species identification, relatedness analysis, and population structure studies. Suitable for research in environmental microbiology, medical microbiology, and metagenomics.

3. Protein Family Evolution and Functional Inference

Analyze evolutionary relationships within protein families to identify conserved sites, functional divergence, and signals of positive selection. By combining phylogenetic trees with other functional data, infer the function of unknown proteins and their evolutionary origins.

Core Functions

1. Multiple Sequence Alignment and Preprocessing (MAFFT + TrimAl)

Use MAFFT for high-quality multiple sequence alignment, supporting various modes from high precision (linsi/einsi) to ultra-large scale (fftns/auto). Integrate TrimAl for alignment quality control to automatically remove unreliable alignment columns and improve the accuracy of subsequent tree construction.

2. Maximum Likelihood Tree Inference (IQ-TREE 2 / FastTree)

IQ-TREE 2 offers automatic model selection (-m TEST), ultrafast bootstrap support calculation (-B 1000), and molecular clock analysis. It is suitable for medium and small datasets (<5000 sequences). FastTree is designed for large datasets (>1000 sequences), providing a 10–100× speedup while maintaining reasonable accuracy.

3. Phylogenetic Tree Visualization and Analysis (ETE3)

Based on the ETE3 Python library for phylogenetic tree operations, rooting (midpoint rooting or outgroup rooting), branch trimming, and statistical computations. Supports rectangular and circular tree rendering, and allows custom coloring by species, sample type, etc., to generate publication-grade visualizations.

Frequently Asked Questions

What data formats are needed for phylogenetic analysis?

You need sequence files in FASTA format (e.g., .fasta, .fa, .fna), which can be nucleotide sequences (.nt) or amino acid sequences (.aa). Sequences must be quality-controlled to remove low-quality and redundant sequences. For molecular clock analysis, you also need a text file containing sample collection dates (dates.txt).

How do I choose between IQ-TREE and FastTree?

Choose based on dataset size and requirements:

IQ-TREE 2: <5000 sequences, requires high precision, automatic model selection, bootstrap support values, or molecular clock analysis

FastTree: >1000 sequences, needs rapid preview or very large datasets with limited time budget

Recommended workflow: Use FastTree first for a quick overview of the overall structure, then use IQ-TREE for detailed analysis of key branches

How do I interpret bootstrap support values on a phylogenetic tree?

Bootstrap support values indicate the statistical reliability of a branch (0–100):

≥95%: Very credible branch; results are robust

70–94%: Moderately credible branch; interpret with caution

&lt;70%: Low branch reliability; not recommended as a basis for conclusions

High bootstrap values typically require a sufficient number of sequences, good alignment quality, and an appropriate evolutionary model. If overall support values are low, check alignment quality, increase bootstrap replicates, or try different models.