Statistics Papers

Document Type

Technical Report

Date of this Version

6-1-2015

Publication Source

Biometrika

Volume

102

Issue

2

Start Page

247

Last Page

266

DOI

10.1093/biomet/asu074

Abstract

Model organisms and human studies have led to increasing empirical evidence that interactions among genes contribute broadly to genetic variation of complex traits. In the presence of gene-by-gene interactions, the dimensionality of the feature space becomes extremely high relative to the sample size. This imposes a significant methodological challenge in identifying gene-by-gene interactions. In the present paper, through a Gaussian graphical model framework, we translate the problem of identifying gene-by-gene interactions associated with a binary trait

Copyright/Permission Statement

This is a pre-copyedited, author-produced PDF of an article accepted for publication in Biometrika following peer review. The version of record [Xia, Y., Cai, T., & Cai, T.T. Testing Differential Networks with Applications to the Detection of Gene-Gene Interactions. Biometrika 102, no. 2: pp. 247-266] is available online at: http://dx.doi.org/10.1093/biomet/asu074

Keywords

differential network, false discovery rate, Gaussian graphical model, gene-by-gene interaction, highdimensional precision matrix, large scale multiple testing

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Date Posted: 25 October 2018

This document has been peer reviewed.