The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Online Program Home
Abstract Details
Activity Number:
|
181
|
Type:
|
Contributed
|
Date/Time:
|
Monday, July 30, 2012 : 10:30 AM to 12:20 PM
|
Sponsor:
|
Section on Bayesian Statistical Science
|
Abstract - #304767 |
Title:
|
Bayesian Hierarchical Graph Models for Phylogeography
|
Author(s):
|
Gabriela Cybis*+ and Marc A Suchard and Janet Sinsheimer
|
Companies:
|
University of California at Los Angeles and University of California at Los Angeles and University of California at Los Angeles
|
Address:
|
3770 Keystone Ave, Los Angeles, CA, 90034, United States
|
Keywords:
|
Bayesian Phylogenetics ;
Hierarchical Model ;
Phylodynamics
|
Abstract:
|
Viral pathogens kill every year millions of people worldwide. Accurate information on their dispersion process is important for the formulation of better public health policies. Bayesian phylogeographic methods integrate geographic and evolutionary modeling to assess such information. We enhance the potentialities of existing phylogeographic methods by integrating multiple datasets in a hierarchical setting. In our model there are n exchangeable strata consisting of viral sequences and locations; each evolving along a phylogenetic tree and according to a conditionally independent geographic process. At the hierarchical level, a random graph summarizes the overall dispersion process by informing which migration rates between sampling locations are likely to be nonnegative in the strata. This approach can then be used to test differences and commonalities between strata. Our method represents an appropriate framework for analyzing inherently hierarchical datasets, such as multilocus data. We use a data set consisting of multiple subtypes of Dengue Virus in the Americas to showcase the potentialities of our method.
|
The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
Back to the full JSM 2012 program
|
2012 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.