New sequencing and genotyping technologies are making it possible to determine relatively complete genotype information for individuals. These data are being used to identify quantitative loci which are responsible for increased risk of developing diseases and that are responsible for variation in other complex phenotypes. We are developing novel Bayesian statistical approaches for this purpose for both individual marker and multi-locus models. We have applied our approaches in a variety of experimental mapping designs and we are currently collaborating with other research groups to identify loci responsible for variation in a number of complex phenotypes including human lung disease, smoking responsive gene expression, blood disease in dogs, Drosophila gene expression, and circadian clock variation in yeast.