Using Evolutionary Computing on Consumer Graphics Hardware for Epistasis Analysis in Human Genetics
A. Nicholas, Casey S. Greene, Jason H. Moore · 2009
Biological systems are both complex and robust. Because of this epistasis, or gene-gene interactions, are thought to be a ubiquitous component of common human diseases. Unfortunately, due to the non-linear nature of these interactions, detecting and characterizing epistasis requires algorithms which are combinatorial in complexity. One such algorithm is Multifactor Dimensionality Reduction (MDR). Expert knowledge guided evolutionary computing wrappers around MDR have previously been shown to be a powerful way to eciently analyze datasets for interactions. Evolutionary computing can eectively address some of the challenges these datasets present. Unfortunately examining the statistical significance of results requires permutation testing, which increases the computation requirements by a factor of 1000. Here we implement an expert knowledge guided ant system on graphics processing units (GPUs) and show that the GPU implementation makes the rigorous statistical analysis of large datasets practical.