  The variance component tests used in genomewide association studies of
thousands of individuals become computationally exhaustive when multiple traits
are analysed in the context of omics studies. We introduce two high-throughput
algorithms -- CLAK-CHOL and CLAK-EIG -- for single and multiple phenotype
genome-wide association studies (GWAS). The algorithms, generated with the help
of an expert system, reduce the computational complexity to the point that
thousands of traits can be analyzed for association with millions of
polymorphisms in a course of days on a standard workstation. By taking
advantage of problem specific knowledge, CLAK-CHOL and CLAK-EIG significantly
outperform the current state-of-the-art tools in both single and multiple trait
analysis.
