Check this box to perform principal component regression where principal components (PCs) are calculated from all SNPs (or collapsed rare variant loci) with the same value of the Annotation Analysis Group Variable, and the PCs with the largest eigenvalues are included in a regression model similar to the multiple- locus regression model (with SNP genotype replaced by the PCs) (Gauderman et al. 2007, Wang and Abbot 2008). The number of PCs to include in the model is determined by the Maximum Number of Principal Components and Cumulative Proportion of Variation to Explain with Principal Components parameters below. You can adjust for covariates or class effects by specifying them on the Model Variables tab. Statistics for the joint test of all PCs included in the model are reported.
