This project will improve the robustness of error analysis and correction by developing new root-cause error analysis methods and hybrid error-correction algorithms accelerated via FPGA or GPU implementations. Variant calling will be improved by both suppressing errors and building new machine-learning based techniques that would work with clinical workflows.