JSM 2015 Preliminary Program

Online Program Home
My Program

Abstract Details

Activity Number: 604
Type: Contributed
Date/Time: Wednesday, August 12, 2015 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics in Imaging
Abstract #317445
Title: Improving Signal-to-Noise Ratio in Large-Scale Multiple Testing with High-Dimensional Covariates
Author(s): Chintan Mehta* and Heping Zhang
Companies: Yale University and Yale University
Keywords: Principal component analysis ; Factor analysis ; Multiple testing ; Large-Scale Inference ; Feature ranking and selection ; Imaging
Abstract:

In genome-wise association studies (GWAS), inferring the significance of a large number of genomic markers on a clinical phenotype is hindered by the multiple testing problem, in which controlling Type I error significantly deteriorates the power of tests. Test power can be improved by augmenting signal-to-noise ratio through auxiliary covariates strongly associated with the phenotype. For example, brain imaging data can serve to improve such inference for phenotypes related to mental illness or cognitive ability. In this paper, we develop a systematic method for reducing dimension size in auxiliary data that reduces signal-to-noise ratio in GWAS yielding more powerful tests. After applying principal component analysis on imaging data from a given number of subjects, our method estimates factors for each subject based on thresholded factor loadings. These factors are then employed as covariates while we assess the association genomic markers with the phenotype. We apply this method to the data from the Pediatric, Imagining, and Neurocognitive (PING) study to infer associations between genomic markers, anatomical regions in the brain, and cognitive traits.


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

Back to the full JSM 2015 program





For program information, contact the JSM Registration Department or phone (888) 231-3473.

For Professional Development information, contact the Education Department.

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

2015 JSM Online Program Home