|
Activity Number:
|
143
- Some New Perspectives and Developments in Biostatistical Research in the Era of Data Science
|
|
Type:
|
Invited
|
|
Date/Time:
|
Monday, July 30, 2018 : 10:30 AM to 12:20 PM
|
|
Sponsor:
|
SSC
|
|
Abstract #325465
|
Presentation
|
|
Title:
|
Combining Phenotypes, Genotypes, and Genealogies to Fine-Map Trait-Influencing Variants on the Genome
|
|
Author(s):
|
Jinko Graham*
|
|
Companies:
|
Simon Fraser University
|
|
Keywords:
|
association;
genetic variation;
disease traits;
gene genealogies;
ancestral clustering;
the coalescent
|
|
Abstract:
|
A basic tenet of statistical genetics is that shared ancestry leads to trait similarities in individuals. Related individuals share segments of their genome, derived from a single DNA segment in a common ancestor. The coalescent is a popular mathematical model of the shared ancestry that represents the relationships amongst segments as a set of binary trees along the genome. While these ancestral trees cannot be observed directly, the genetic-marker data enable us to sample from their posterior distribution. To each tree sampled from the posterior distribution, we may apply statistical tests of ancestral clustering with trait values. The distribution of p-values from these tests summarizes the trait's ancestral association at a given genomic location and is informative for mapping trait-influencing variants. In this talk, I will present preliminary results from applying these ideas to real datasets.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2018 program
|
