Sib-pair linkage analysis of complex human diseases has become a method of choice in modern human genetic studies, especially for the diseases with a late age at onset. The traditional parametric methods for sib pair ...Sib-pair linkage analysis of complex human diseases has become a method of choice in modern human genetic studies, especially for the diseases with a late age at onset. The traditional parametric methods for sib pair data need to take the categorical nature of a disease phenotype into account and to explicitly model the non-linear relationship between the discrete phenotype and genetic determinants, or to force their relationship to be linear. The first approach is desirable theoretically, but explicitly modeling the sophisticated genetic architecture of a complex disease can be prohibitively complex and computational demand is high. The second approach, typically a linear regression, relies on a large sample theory and is not appropriate. In this paper, we propose to apply Analysis of Variance (ANOVA) to sib pair linkage analysis of complex human diseases. This approach has avoided building the complicated relationship between the phenotype (the affection group or status of a sib pair) and the underlying genetic determinant (identical-by-decent (IBD) values etc). We have explored its statistical efficiency and properties in sibpair linkage analysis of ordinal complex human diseases via simulation. The simulation suggests that it is a powerful approach for locating genes that presumably control phenotypic expression of complex human diseases.展开更多
文摘Sib-pair linkage analysis of complex human diseases has become a method of choice in modern human genetic studies, especially for the diseases with a late age at onset. The traditional parametric methods for sib pair data need to take the categorical nature of a disease phenotype into account and to explicitly model the non-linear relationship between the discrete phenotype and genetic determinants, or to force their relationship to be linear. The first approach is desirable theoretically, but explicitly modeling the sophisticated genetic architecture of a complex disease can be prohibitively complex and computational demand is high. The second approach, typically a linear regression, relies on a large sample theory and is not appropriate. In this paper, we propose to apply Analysis of Variance (ANOVA) to sib pair linkage analysis of complex human diseases. This approach has avoided building the complicated relationship between the phenotype (the affection group or status of a sib pair) and the underlying genetic determinant (identical-by-decent (IBD) values etc). We have explored its statistical efficiency and properties in sibpair linkage analysis of ordinal complex human diseases via simulation. The simulation suggests that it is a powerful approach for locating genes that presumably control phenotypic expression of complex human diseases.
