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A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
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Published on: December 10, 2012

Fully Bayesian tests of neutrality using genealogical summary statistics.

Alexei J Drummond1, Marc A Suchard

  • 1Bioinformatics Institute, University of Auckland, Auckland, New Zealand. alexei@cs.auckland.ac.nz

BMC Genetics
|November 4, 2008
PubMed
Summary

This study introduces a new Bayesian method to test evolutionary neutrality by separating demographic and selection effects. The approach successfully identified non-neutral evolution in human influenza A virus, improving evolutionary analysis.

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Published on: January 16, 2019

Area of Science:

  • Evolutionary biology
  • Population genetics
  • Bioinformatics

Background:

  • Assessing evolutionary neutrality is challenging due to complex mutational and population size models.
  • Existing neutrality tests often conflate violations of these assumptions, complicating interpretation.

Purpose of the Study:

  • To develop a robust method for testing the selective neutrality of molecular evolution.
  • To disentangle the effects of demographic history and natural selection on genetic data.

Main Methods:

  • Utilized posterior predictive simulation with summary statistics of data and model parameters.
  • Employed a model-based Bayesian analysis framework.
  • Applied the method to non-recombining gene genealogies.

Main Results:

  • Demonstrated the method's utility on four real data sets.
  • Identified significant departures from neutrality in human influenza A virus evolution.
  • Successfully controlled for population size variation in neutrality testing.

Conclusions:

  • The Bayesian approach effectively separates demographic and selection influences.
  • The method enhances sensitivity by integrating multiple summary statistics.
  • Applicable to temporally spaced data where traditional methods are limited.