title: A robust statistical method for association-based eQTL analysis.
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.
  
  
  METHODS
  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 the new method were tested through an intensive computer simulation study and an association-based genome-wide mapping of expression quantitative trait loci in genetically divergent human populations.
  
  
  CONCLUSIONS
  The analyses show that the new method confers an improved statistical power for detecting genuine genetic association in subpopulations and an effective control of spurious associations stemmed from population structure when compared with other two popularly implemented methods in the literature of GWAS.
authors.affiliation: School of Biosciences, University of Birmingham, Birmingham, United Kingdom.
authors.forename: Ning
authors.initials: N
authors.lastname: Jiang
authors.forename: Minghui
authors.initials: M
authors.lastname: Wang
authors.forename: Tianye
authors.initials: T
authors.lastname: Jia
authors.forename: Lin
authors.initials: L
authors.lastname: Wang
authors.forename: Lindsey
authors.initials: L
authors.lastname: Leach
authors.forename: Christine
authors.initials: C
authors.lastname: Hackett
authors.forename: David
authors.initials: D
authors.lastname: Marshall
authors.forename: Zewei
authors.initials: Z
authors.lastname: Luo
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D005787:Gene Frequency; D005819:Genetic Markers / Q000235:genetics; D005828:Genetics, Population / Q000379:methods; D055106:Genome-Wide Association Study / Q000379:methods*; D006801:Humans; D015810:Linkage Disequilibrium; D008957:Models, Genetic; D011110:Polymorphism, Genetic; D040641:Quantitative Trait Loci / Q000235:genetics*; D015203:Reproducibility of Results
chemical_list: D005819:Genetic Markers