Analysis of gene-gene interactions using gene-trait similarity regression

Xin Wang, Michael P. Epstein, Jung Ying Tzeng

研究成果: Article同行評審

5 引文 斯高帕斯(Scopus)

摘要

Objective: Gene-gene interactions (G×G) are important to study because of their extensiveness in biological systems and their potential in explaining missing heritability of complex traits. In this work, we propose a new similarity-based test to assess G×G at the gene level, which permits the study of epistasis at biologically functional units with amplified interaction signals. Methods: Under the framework of gene-trait similarity regression (SimReg), we propose a gene-based test for detecting G×G. SimReg uses a regression model to correlate trait similarity with genotypic similarity across a gene. Unlike existing gene-level methods based on leading principal components (PCs), SimReg summarizes all information on genotypic variation within a gene and can be used to assess the joint/interactive effects of two genes as well as the effect of one gene conditional on another. Results: Using simulations and a real data application to the Warfarin study, we show that the SimReg G×G tests have satisfactory power and robustness under different genetic architecture when compared to existing gene-based interaction tests such as PC analysis or partial least squares. A genome-wide association study with approx. 20,000 genes may be completed on a parallel computing system in 2 weeks.

原文English
頁(從 - 到)17-26
頁數10
期刊Human Heredity
78
發行號1
DOIs
出版狀態Published - 2014 七月

All Science Journal Classification (ASJC) codes

  • Genetics
  • Genetics(clinical)

指紋 深入研究「Analysis of gene-gene interactions using gene-trait similarity regression」主題。共同形成了獨特的指紋。

引用此