One area of particular interest in statistical genetics is in developing novel methods to enhance the analysis and interpretation of summary association statistics. Currently, it is a standard practice for consortia studies to release summary association statistics publically. These datasets have become an invaluable resource. Numerous methods have been developed to leverage this information to conduct fine mapping [Kichaev et al., 2014], perform gene‐level association tests [Lee et al., 2013; Liu et al., 2014], and infer causal relationships between biomarkers and diseases [Burgess et al., 2014; Do et al., 2013]. There is an ever‐increasing need for new methods and tools to more effectively use these datasets.
