Online Program Home
  My Program

Abstract Details

Activity Number: 18 - Optimal Transport and Scalable Bayes: A Fruitful Synergy?
Type: Topic Contributed
Date/Time: Sunday, July 30, 2017 : 2:00 PM to 3:50 PM
Sponsor: Section on Bayesian Statistical Science
Abstract #322989
Title: Nonparametric Bayes Multiresolution Testing for High-Dimensional Rare Events
Author(s): Jyotishka Datta* and David Dunson
Companies: University of Arkansas, Fayetteville and Duke University
Keywords: NP-Bayes ; Multiscale ; Rare events ; Dirichlet Process ; Poisson-Gamma ; Next-generation sequencing
Abstract:

In a variety of application areas, there is interest in assessing evidence of differences in the intensity of event realizations between groups. For example, in cancer genomic studies collecting data on rare variants, the focus is on assessing whether and how the variant profile changes with disease sub-type. We develop multiresolution nonparametric Bayes tests for differential mutation rates across groups. The multiresolution approach yields fast and accurate detection of spatial clusters of rare variants, and our nonparametric Bayes framework provides great flexibility for modeling the intensities of rare variants. Some theoretical properties are also assessed, including weak consistency of our Dirichlet Process-Poisson-Gamma mixture over multiple resolutions. Simulation studies illustrate excellent small sample properties relative to competitors, and we apply the method to detect rare variants related to common variable immunodeficiency from whole exome sequencing data on 215 patients and over 60,027 control subjects.


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

Back to the full JSM 2017 program

 
 
Copyright © American Statistical Association