title: Fast eQTL Analysis for Twin Studies.
abstract: Twin data are commonly used for studying complex psychiatric disorders, and mixed effects models are one of the most popular tools for modeling dependence structures between twin pairs. However, for eQTL (expression quantitative trait loci) data where associations between thousands of transcripts and millions of single nucleotide polymorphisms need to be tested, mixed effects models are computationally inefficient and often impractical. In this paper, we propose a fast eQTL analysis approach for twin eQTL data where we randomly split twin pairs into two groups, so that within each group the samples are unrelated, and we then apply a multiple linear regression analysis separately to each group. A score statistic that automatically adjusts the (hidden) correlation between the two groups is constructed for combining the results from the two groups. The proposed method has well-controlled type I error. Compared to mixed effects models, the proposed method has similar power but drastically improved computational efficiency. We demonstrate the computational advantage of the proposed method via extensive simulations. The proposed method is also applied to a large twin eQTL data from the Netherlands Twin Register.
authors: Department of Biostatistics, University of North Carolina, Chapel Hill, North, Carolina, United States of America.
authors: Zhaoyu
authors: Z
authors: Yin
authors: Department of Psychiatry, University of North Carolina, Chapel Hill, North Carolina, United States of America.
authors: Kai
authors: K
authors: Xia
authors: School of Public Health, Harvard, Boston, Massachusetts, United States of America.
authors: Wonil
authors: W
authors: Chung
authors: Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America.
authors: Patrick F
authors: PF
authors: Sullivan
authors: Department of Biostatistics, University of North Carolina, Chapel Hill, North, Carolina, United States of America.
authors: Fei
authors: F
authors: Zou
mesh_terms: D000465:Algorithms; D019295:Computational Biology; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D006801:Humans; D008957:Models, Genetic; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D040641:Quantitative Trait Loci
keywords: high correlation; matrix representation; mixed effects model; score statistic; twin eQTL data