Online Program Home
My Program

Abstract Details

Activity Number: 21 - Aligning Data Normalization with Analysis Goals for Reproducible Research
Type: Topic Contributed
Date/Time: Sunday, July 28, 2019 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract #303012
Title: Multiple Testing Under Dependence and Non-Sparsity with Applications in Genomics and Toxicology
Author(s): Hongyuan Cao* and Shyamal Peddada and Li-Xuan Qin
Companies: Florida State University and University of Pittsburgh and Memorial Sloan Kettering Cancer Center

High throughput technologies enable simultaneous inference of complex high dimensional data. An acute problem is the multiple testing adjustment. Most existing literature examine the problem under independence and sparsity assumptions. We propose a multiple testing procedure to incorporate dependence and non-sparsity features inherent in many high dimensional data, such as microRNA in genomics and quantitative high throughput screening (qHTS) assays in toxicology.

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

Back to the full JSM 2019 program