Gene-trait similarity regression for multimarker-based association analysis.
We propose a similarity-based regression method to detect associations between traits and multimarker genotypes. The model regresses similarity in traits for pairs of "unrelated" individuals on their haplotype similarities, and detects the significance by a score test for which the limiting distribution is derived. The proposed method allows for covariates, uses phase-independent similarity measures to bypass the needs to impute phase information, and is applicable to traits of general types (e.g., quantitative and qualitative traits). We also show that the gene-trait similarity regression is closely connected with random effects haplotype analysis, although commonly they are considered as separate modeling tools. This connection unites the classic haplotype sharing methods with the variance-component approaches, which enables direct derivation of analytical properties of the sharing statistics even when the similarity regression model becomes analytically challenging.
Tzeng
Jung-Ying
JY
Department of Statistics, North Carolina State University, Raleigh, North Carolina 27695, USA. jytzeng@stat.ncsu.edu
Zhang
Daowen
D
Chang
Sheng-Mao
SM
Thomas
Duncan C
DC
Davidian
Marie
M
D002874:Chromosome Mapping / Q000379:methods*; D003198:Computer Simulation; D008040:Genetic Linkage / Q000235:genetics*; D005819:Genetic Markers / Q000235:genetics*; D006239:Haplotypes / Q000235:genetics*; D006801:Humans; D008957:Models, Genetic; D015233:Models, Statistical; D040641:Quantitative Trait Loci / Q000235:genetics*; D012044:Regression Analysis
D005819:Genetic Markers