a robust statistical method for association-based eqtl analysis一个健壮的统计方法为协会eqtl分析.pdfVIP

A Robust Statistical Method for Association-Based eQTL Analysis 1,3 1 1 2 1 3 Ning Jiang , Minghui Wang , Tianye Jia , Lin Wang , Lindsey Leach , Christine Hackett , David Marshall4, Zewei Luo1,2* 1 School of Biosciences, University of Birmingham, Birmingham, United Kingdom, 2 Laboratory of Population and Quantitative Genetics, Institute of Biostatistics, Fudan University, Shanghai, China, 3 BioSS, Invergowrie, Dundee, Scotland, United Kingdom, 4 Scottish Crop Research Institute, Invergowrie, Dundee, Scotland, United Kingdom Abstract Background: It has been well established that theoretical kernel for recently surging genome-wide association study (GWAS) is statistical inference of linkage disequilibrium (LD) between a tested genetic marker and a putative locus affecting a disease trait. However, LD analysis is vulnerable to several confounding factors of which population stratification is the most prominent. Whilst many methods have been proposed to correct for the influence either through predicting the structure parameters or correcting inflation in the test statistic due to the stratification, these may not be feasible or may impose further statistical problems in practical implementation. Methodology: We propose here a novel statistical method to control spurious LD in GWAS from population structure by incorporating a control marker into testing for significance of genetic association of a polymorphic marker with phenotypic variation of a complex trait. The method avoids the need of structure prediction which may be infeasible or inadequate in practice and accounts properly for a varying effect of population stratification on different regions of the genome under study. Utility and statistical properties of