Hundreds of thousands of SNP markers are being generated with the purpose of carrying out case-control association studies for complex traits, which are thought to be due to multiple underlying susceptibility genes. The number of markers is typically much larger than the number of observations so that joint analysis of marker genotypes and their interactions is not feasible. We discuss a two-stage approach to first select a small subset of markers and then model the effects of the selected markers on disease. Examples of two procedures for marker selection are given with subsequent modeling of main and interaction effects. The approaches are applied to a data set with 89 SNPs in lieu of a genome screen with many more markers.
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