應用統計分析方法探討罕見及一般性致病之基因變異(3/3)

Despite of the success of genome-wide association studies (GWAS) in detecting common variants (minor allele frequency (MAF) >5%) associated with common diseases, the proportion of heritability explained by common variants is only modest. Many suggested that rare variants also contribute to the genetic architecture of disease and the combination of GWAS and sequencing would be a good technique for studying diseases. In this project, we consider designs and tests for detecting group-wise association between multiple rare (and common) variants in a locus with a genetically heterogeneous disease. Our main research topics include: (1) considering a family-trio design and association tests based on combining association signals across all variants within a locus, (2) studying the effect of population stratification of the collapsing tests in case-control studies and suggesting a bias-correction method, (3) suggesting a method for exploiting locus-locus interaction information in detecting rare and common variants within a locus. We shall compare power performance of the single-marker test, multiple-marker test and proposed novel tests by simulations under allelic or locus heterogeneity models. We shall also study a phenomenon called synthetic genome-wide associations.