MAMMLE: A Framework for Phylogeny Estimation Based on Multiobjective Application-aware Multiple Sequence Alignment and Maximum Likelihood Ensemble
- 27 January 2023
- journal article
- research article
- Published by Mary Ann Liebert Inc in Journal of Computational Biology
- Vol. 30 (3), 245-249
- https://doi.org/10.1089/cmb.2021.0533
Abstract
Motivation: Phylogenetic trees are often inferred from a multiple sequence alignment (MSA) where the tree accuracy is heavily impacted by the nature of estimated alignment. Carefully equipping an MSA tool with multiple application-aware objectives positively impacts its capability to yield better trees. Results: We introduce Multiobjective Application-aware Multiple Sequence Alignment and Maximum Likelihood Ensemble (MAMMLE), a framework for inferring better phylogenetic trees from unaligned sequences by hybridizing two MSA tools [i.e., Multiple Sequence Comparison by Log-Expectation (MUSCLE) and Multiple Alignment using Fast Fourier Transform (MAFFT)] with multiobjective optimization strategy and leveraging multiple maximum likelihood hypotheses. In our experiments, MAMMLE exhibits 5.57% (4.77%) median improvement (deterioration) over MUSCLE on 50.34% (37.41%) of instances.Keywords
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