Genome Wide Association Studies (GWAS) have identified many genomic regions or loci which harbor genetic variants that affect traits. However, within each of these regions, there are many genetic variants which as associated with the trait, yet most of these variants do not have a direct effect on the trait. The process of identifying the actual variant in the region which has an effect on the disease is referred to as “fine mapping.” In addition to finding the actual variants affecting a disease, fine mapping also seeks to address questions that are related to the genetic basis of disease. First, how many causal variants does a locus contain? A disease could be caused by one, single variant or multiple variants that independently affect disease status. We refer to the latter phenomenon as allelic heterogeneity (AH). Second, when analyzing results from multiple GWASes, are the same causal variants affect both traits or are different variants effecting each trait? Differentiating between shared and distinct causal variants is referred to as Colocalization. In this talk, I present recent work from our group on fine mapping methods which provides a framework for identifying causal variants and can be applied to discover and quantify allelic heterogeneity and colocolization.