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Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

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Published on: August 14, 2018

Naive binning improves phylogenomic analyses.

Md Shamsuzzoha Bayzid1, Tandy Warnow

  • 1Department of Computer Science, The University of Texas at Austin, Austin, TX 78712, USA.

Bioinformatics (Oxford, England)
|July 12, 2013
PubMed
Summary
This summary is machine-generated.

Species tree estimation using naive binning improves phylogenomic analysis accuracy and scalability, especially when gene trees are poorly estimated due to incomplete lineage sorting (ILS). This method enhances both *BEAST and summary methods.

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Published on: December 10, 2012

Area of Science:

  • Phylogenomics
  • Computational Biology
  • Evolutionary Biology

Background:

  • Species tree estimation is challenged by incomplete lineage sorting (ILS).
  • Performance of existing methods is poorly understood with inaccurate gene trees.
  • Inadequate phylogenetic signal in gene trees complicates accurate species tree inference.

Purpose of the Study:

  • To evaluate species tree estimation methods under ILS with poorly estimated gene trees.
  • To compare the performance of *BEAST, concatenation, and various summary methods.
  • To propose and assess a novel method for improving scalability and accuracy.

Main Methods:

  • Simulated datasets with varying levels of ILS were used.
  • Methods evaluated included *BEAST, concatenated analysis, BUCKy, MP-EST, minimize deep coalescence, matrix representation with parsimony, and greedy consensus.
  • A new approach involving partitioning genes into sets to create 'supergenes' was proposed and tested.

Main Results:

  • *BEAST and concatenated analysis showed excellent accuracy, outperforming other methods.
  • *BEAST's accuracy stems from co-estimating gene and species trees but is computationally intensive.
  • The proposed naive binning technique improved *BEAST's scalability without compromising accuracy and boosted summary method accuracy.

Conclusions:

  • Naive binning is an effective strategy for enhancing species tree estimation in phylogenomics.
  • This approach addresses computational limitations of methods like *BEAST.
  • The findings offer practical improvements for analyzing large genomic datasets with ILS.