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Activity Number: 177
Type: Contributed
Date/Time: Monday, August 1, 2016 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract #320913 View Presentation
Title: Biologically Pathway Information Incorporated Structured Model
Author(s): Xuebei An* and Jianhua Hu and Kim-Anh Do
Companies: MD Anderson Cancer Center and MD Anderson Cancer Center and MD Anderson Cancer Center
Keywords: high-dimensional omics data ; integrative analysis ; network-based penalized regression ; pathway information incorporation

High-dimensional omic data derived from different technological platforms have been extensively used to facilitate comprehensive understanding of disease mechanisms. It is also recognized that incorporation of some biological information (e.g. pathway) in the analysis of omic data can lead to more accurate and interpretable results. We propose a statistical framework of shared informative factor models that can jointly analyze multi-platform omic data, explore their associations with a disease phenotype, and incorporate pathway information while integration. Extensive simulation studies demonstrate the performance of the proposed method in terms of biomarker detection and prediction accuracy. We also illustrate the applicability of the proposed method using a TCGA kidney cancer data set. The association of mRNA expression and protein expression with survival of kidney cancer patients is explored.

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

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