Online Program Home
My Program

Abstract Details

Activity Number: 480 - Novel Statistical Methods for Bioinformatics and Computational Biology
Type: Invited
Date/Time: Wednesday, July 31, 2019 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Genomics and Genetics
Abstract #300521 Presentation
Title: Bayesian Detection of Convergent Rate Changes of Conserved Noncoding Elements on Phylogenetic Trees
Author(s): Scott V Edwards and Jun S. Liu* and Zhirui Hu and Timothy B Sackton
Companies: Harvard University and Harvard University and Harvard University and Harvard University
Keywords: Markov chain Monte Carlo; conserved elements; trait loss

Conservation of DNA sequence over evolutionary time is a strong indicator of function, and gain or loss of sequence conservation can be used to infer changes in function across a phylogeny. Changes in evolutionary rates on particular lineages in phylogeny can indicate shared functional shifts, and thus can be used to detect genomic correlates of phenotypic convergence. However, existing methods do not allow easy detection of patterns of rate variation, which causes challenges for detecting convergent rate shifts or other complex evolutionary scenarios. Here, we introduce PhyloAcc, a new Bayesian method to model substitution rate changes in conserved elements across a phylogeny. The method can handle diverse evolutionary patterns and complex patterns of convergence, assumes a latent conservation state for each branch on the phylogenetic tree, estimates element-wise substitution rates per state, and detects changes of substitution rate as the posterior probability of a state switch. Simulations show that PhyloAcc can outperform existing approaches in various aspects

Authors who are presenting talks have a * after their name.

Back to the full JSM 2019 program