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Updated: Jun 4, 2025

A Practical Guide to Phylogenetics for Nonexperts

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Published on: February 5, 2014

MixtureFinder: Estimating DNA Mixture Models for Phylogenetic Analyses.

Huaiyan Ren^1,2, Thomas K F Wong^1,2, Bui Quang Minh¹

¹School of Computing, College of Engineering, Computing and Cybernetics, Australian National University, Canberra, ACT 2600, Australia.

Molecular Biology and Evolution

|December 23, 2024

Summary

This summary is machine-generated.

Mixture models offer a better approach than partitioned models for analyzing DNA sequence evolution heterogeneity. A new algorithm, MixtureFinder, optimizes mixture models, improving phylogenetic analyses.

Keywords:

mixture model molecular evolution phylogenetics

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Published on: August 16, 2017

Area of Science:

Phylogenetics and evolutionary biology
Computational biology and bioinformatics

Background:

Molecular evolution models are crucial for phylogenetic studies.
Partitioned and mixture models address heterogeneity in DNA sequence alignments.
Partitioned models assume site subsets share a common evolutionary process, while mixture models do not require pre-specified subsets.

Purpose of the Study:

To evaluate the assumption of a single common process within user-specified subsets in partitioned models.
To develop and validate an algorithm for optimizing mixture models in DNA sequence evolution analysis.
To provide a tool for selecting the optimal number of classes for mixture models.

Main Methods:

Assessed the validity of the single common process assumption for partitioned models using data.
Designed, implemented, and tested the MixtureFinder algorithm.
Applied MixtureFinder to simulated and empirical datasets for phylogenetic analysis.

Main Results:

The assumption of a single common process within user-specified subsets of partitioned models is not supported by data.
The developed MixtureFinder algorithm effectively selects the optimal number of classes for mixture models.
MixtureFinder demonstrates robust performance on both simulated and empirical datasets.

Conclusions:

Mixture models are a more appropriate framework than partitioned models for analyzing heterogeneity in DNA sequence evolution.
The MixtureFinder algorithm is a valuable tool for optimizing mixture models in phylogenetic studies.
MixtureFinder is integrated into IQ-TREE2, facilitating its use in future research.