This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 512
Type: Contributed
Date/Time: Wednesday, August 4, 2010 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #308568
Title: Determining the Genic Contribution to Disease by Evaluating Component SNPs
Author(s): Benjamin Alan Goldstein*+ and Alan Hubbard and Lisa Barcellos
Companies: University of California, Berkeley and University of California, Berkeley and University of California, Berkeley
Address: 1400 Technology Lane, Petaluma, CA, 94954, USA
Keywords: Genetic Epidemiology ; Machine Learning ; Super Learner

SNP variation can lead to differences in levels of gene expression or function of protein products and consequentially phenotypic variation. Typically, disease associated SNPs are identified using marginal chi-square tests, and more recently via machine learning procedures. Overall, this approach ignores composite properties of variation within a gene that may be more explanatory of function. Using a procedure motivated by Super Learning, we propose a method to define a functional form for the effect of multiple SNPs within a gene on an outcome. The outcome is regressed on these functions to examine the relationship between genes and disease status. Simulation results show this method is able to highlight associations that would otherwise be missed. We apply this method to genetic data from an autoimmune disease study and compare results with those obtained from more traditional methods.

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 2010 program

2010 JSM Online Program Home

For information, contact or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.