Dr. Teer's research interests are focused on developing methods to analyze, interpret and visualize massively-parallel sequencing information in cancer genetics. This includes developing and applying computational methods and graphical tools to better detect genetic variations from sequencing data, understand the functional context of sequence changes, and visualize the results of large-scale genomics studies.