Title: Identifying cis/trans-acting expression quantitative trait loci (eQTL)

Authors: Mingon Kang; Dongchul Kim; Chunyu Liu; Jean Gao

Addresses: Department of Computer Science, Kennesaw State University, Marietta, GA, USA ' Department of Computer Science, University of Texas - Rio Grande Valley, Edinburg, TX, USA ' Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA ' Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX, USA

Abstract: Expression Quantitative Trait Loci (eQTL) studies have played an important role in discovering novel susceptibility genes and regulatory mechanisms of human diseases. High-throughput microarray technologies allow to measure thousands of gene expressions at the same time, and the advance enables one to capture the insight of the genetic architecture of gene expression. A number of multivariate methods have been proposed to identify loci associated to gene expression taking into account interactive effects and relationships between the units. However, the large data tend to increase false positives in the studies. We propose a Cis/Trans eQTL Association Mapping (CTAM) method to (a) take co-expressed genes without clustering or partitioning techniques, (b) build a mathematical model for cis- and trans-eQTL based on biological prior knowledge, and (c) identify significant disease-associated genes. The power to detect both joint effect and group effect of SNPs and gene expressions is assessed in the simulation studies. We also applied it to a study of psychiatric disorder diseases data. CTAM detects associations between cis/trans-acting eQTLs and genes.

Keywords: eQTL analysis; cis/trans-acting eQTL; multivariate.

DOI: 10.1504/IJDMB.2017.088524

International Journal of Data Mining and Bioinformatics, 2017 Vol.19 No.1, pp.1 - 18

Received: 11 May 2017
Accepted: 20 May 2017
Published online: 11 Dec 2017 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article