Enhancing the usability and performance of structured association mapping algorithms using automation, parallelization, and visualization in the GenAMap software system.

Structured association mapping is proving to be a powerful strategy to find genetic polymorphisms associated with disease. However, these algorithms are often distributed as command line implementations that require expertise and effort to customize and put into practice. Because of the difficulty required to use these cutting-edge techniques, geneticists often revert to simpler, less powerful methods.