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QMaker: Fast and Accurate Method to Estimate Empirical Models of Protein Evolution
Bui Quang Minh1,2, Cuong Cao Dang3, Le Sy Vinh3
1School of Computing, Australian National University, 145 Science Road, Acton, ACT 2601, Canberra, Australia.
Systematic Biology
|February 22, 2021
Summary
QMaker is a new, efficient method for estimating amino acid substitution models using maximum likelihood. This tool improves phylogenetic analyses by providing better-fitting models derived from large protein datasets.
Area of Science:
- Computational Biology
- Evolutionary Biology
- Bioinformatics
Background:
- Amino acid substitution models are essential for phylogenetic analyses.
- Current maximum likelihood (ML) methods for estimating these models are often complex and time-consuming.
Purpose of the Study:
- To introduce QMaker, a novel and efficient ML method for estimating general time-reversible Q matrices from large protein datasets.
- To provide a user-friendly tool within IQ-TREE for biologists to estimate their own amino acid substitution models.
Main Methods:
- QMaker employs an efficient ML tree search algorithm.
- It incorporates model selection to address alignment heterogeneity.
- Rate mixture models among sites are considered.
Main Results:
- QMaker was used to derive new empirical general amino acid substitution models from the Pfam database.
- Five clade-specific models (mammals, birds, insects, yeasts, plants) were also estimated.
- The new models demonstrate improved data-model fit and can impact phylogenetic tree topology inference.
Conclusions:
- QMaker offers a user-friendly and efficient solution for estimating amino acid substitution models.
- The newly developed models enhance the accuracy of phylogenetic inferences.
- The IQ-TREE implementation facilitates broad accessibility for biological research.
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