JSM 2015 Preliminary Program

Online Program Home
My Program

Abstract Details

Activity Number: 130
Type: Contributed
Date/Time: Monday, August 10, 2015 : 8:30 AM to 10:20 AM
Sponsor: IMS
Abstract #316818
Title: Thresholding Tests for Signal Detection on High-Dimensional Count Distributions
Author(s): Yumou Qiu* and Song Xi Chen and Dan Nettleton
Companies: University of Nebraska - Lincoln and Peking University/Iowa State Univeristy and Iowa State University
Keywords: Detection boundary ; Gauss-Hermite quadrature ; Generalized linear model ; Generalized linear mixed model ; Moderate deviation ; RNA-seq data
Abstract:

Motivated by the analysis of RNA sequencing (RNA-seq) data for genes differentially expressed across multiple conditions, we consider detecting rare and faint linear combinations of the regression coefficients (which we call signals) in high-dimensional response variables which are usually count data. More generally, we address the signal detection problem under generalized linear models. We propose a test statistic that carries out a multi-level thresholding on maximum likelihood estimators (MLEs) of the signals, which allows removal of the dimensions with no signals. A Cramer type moderate deviation result for multi-dimensional MLEs is derived, which is needed to obtain the asymptotic distribution of the thresholding test statistic. Extensions to generalized linear mixed models are made, where Gauss-Hermite quadrature is used to approximate the MLEs of such models. Numerical simulations and a case study on maize RNA-seq data are conducted to confirm and demonstrate the proposed testing approaches.


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