Statistics and Its Interface

Volume 4 (2011)

Number 3

A combined $p$-value approach to infer pathway regulations in eQTL mapping

Pages: 389 – 401

DOI: http://dx.doi.org/10.4310/SII.2011.v4.n3.a13

Authors

Yuehua Cui (Department of Statistics and Probability, Michigan State University, East Lansing, Mich., U.S.A.)

Shaoyu Li (Department of Statistics and Probability, Michigan State University, East Lansing, Mich., U.S.A.)

Barry L. Williams (Department of Zoology and Microbiology, Michigan State University, East Lansing, Mich., U.S.A.)

Abstract

The genetic bases of complex traits often involve multiple inherited genetic factors that function in a network basis. By promoting or reducing the expression of functional genes that are directly or indirectly related to a trait, gene regulation has been proposed as a major determinant of trait variation. The combined analysis of genetic and gene expression data, termed genetical genomics analysis or eQTL mapping, holds great promise in disentangling the mechanism of gene regulation. Given that genes function in a network basis, the detection of a genetic system as a whole could shed novel light into the role of gene regulation. We hypothesized that gene expression changes are often caused by the regulation of a set of variants that belongs to a common genetic system (e.g., a gene network or a pathway). We proposed to combine individual signals (e.g., $p$-values) within a genetic system to form an overall signal while considering correlations between variants, with the goal of inferring the role of the whole system in regulating gene expression in an eQTL mapping framework. A Satterthwaite’s approximation method is applied to approximate the distribution of the combined pvalues. Both simulation and real data analysis showed the relative merits of the combined method. Our method provides a novel strategy in addressing questions related to gene regulations from a systems biology perspective.

Keywords

gene regulation, gene network, genetical genomics, pathway regulation, Satterthwaite’s approximation, systems biology

Full Text (PDF format)