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Species Tree Inference Using a Mixture Model.

Ikram Ullah1, Pekka Parviainen2, Jens Lagergren3

  • 1School of Computer Science and Communication, Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden.

Molecular Biology and Evolution
|May 13, 2015
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Summary
This summary is machine-generated.

MixTreEM-DLRS offers a two-phase approach for accurate species tree reconstruction, effectively handling gene duplications and losses. This method is faster than PHYLDOG and more accurate than Duptree for large datasets.

Keywords:
expectation maximizationmammalian phylogenymixture modelphylogeneticsspecies trees

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Area of Science:

  • Computational Biology
  • Phylogenetics
  • Genomics

Background:

  • Species tree reconstruction is crucial in biology and medicine.
  • Gene tree discordance due to duplications and losses complicates species tree inference.
  • Existing probabilistic methods face scalability issues with large datasets.

Purpose of the Study:

  • To develop a scalable and accurate method for species tree reconstruction in the presence of gene duplications and losses.
  • To address the limitations of existing probabilistic and parsimony-based approaches.

Main Methods:

  • A two-phase approach: MixTreEM (Expectation-Maximization) for candidate species tree reconstruction from monocopy genes, followed by PrIME-DLRS for selecting the best tree using the DLRS model.
  • PrIME-DLRS accommodates multicopy gene families by modeling sequence evolution, gene duplication, and loss.
  • Evaluation using synthetic and biological data, compared against PHYLDOG and Duptree.

Main Results:

  • MixTreEM-DLRS demonstrates competitive accuracy with PHYLDOG while running significantly faster.
  • The method outperforms Duptree in accuracy.
  • MixTreEM alone provides a fast and accurate alternative for large datasets.

Conclusions:

  • MixTreEM-DLRS is an efficient and accurate tool for species tree reconstruction, particularly in complex evolutionary scenarios involving gene duplication and loss.
  • The method offers a scalable solution for large-scale phylogenetic analyses.
  • MixTreEM is available for use in selecting target species trees.