Given hundreds of thousands of SNPs per subject, relatives are readily identified and excluded as their presence can lead to inflation of Type 1 error. Similarly, genome-wide data allow identification and control for the most infamous bias of a case-control study, inflation of Type 1 error due to population stratification. This occurs when cases and controls are mismatched by ancestry and disease prevalence differs by ancestry, and has been responsible for numerous false positive findings in the literature. With genome-wide SNP data, it is possible to identify individuals with divergent ancestry (even within a continental population); these individuals can be excluded or a statistical method used to control for this bias.
