The ease of rapid genotyping coupled with massive phenotyping (such as measuring gene expression simultaneously across tens of thousands of gene) presents an exiting challenge for evolutionary statistical genomics. By developing and deploying tools for linking genetic variation with agronomic or medical phenotypes of interest, my group hopes to help experimental geneticists identify genomic regions, genes, and specific mutations underlying complex traits. Several statistical problems that arise in this endeavor include: detecting cryptic population structure in samples of cases and controls, multiple testing from scanning many markers and many phenotypes, and disentangling correlations due to shared regulatory networks of co-regulated genese.