Description: FP growth trees provide a useful way of quickly retrieving associative groups based on supply count or a particular item id. One would need to make multiple queries in order to encounter interesting associations, however, it can become immediately apparent of the interesting associations from just looking at a well encoded FP growth tree visualization. In this talk, I will go through a process of generating and visualizing FP growth trees using a genetic dataset containing active and inactive genetic markers. I will then discuss future work using mpi4py within the FP growth tree generating software for use in supercomputer or multi-processor systems and the work with SAGE3.