1. A computationally-efficient method for identifying a correlation between a single-nucleotide polymorphism (SNP) and a function-valued trait in a genome-wide association study (GWAS), the method comprising: for a plurality of subjects, populating a trait matrix with values of the function-valued trait, a domain matrix with values of a plurality of function domain points, and a genotype matrix with allele values of the SNP; linking the trait matrix, the domain matrix, and the genotype matrix; generating a null model comprising a Gaussian distribution in the trait matrix with mean zero and a first covariance term, the first covariance term being determined in part by a first radial basis function (RBF) kernel applied to the domain matrix and in part by a first length-scale parameter; representing the first covariance term as a first Kronecker product; calculating a first maximum likelihood for the null model; partitioning the matrix into a first partition, a second partition, and a third partition based at least in part on alleles of the SNP; generating an alternative model that sums together Gaussian distributions of the first partition, the second partition, and the third partition of the matrix, each with mean value and a second, third, and fourth covariance term determined in part by a second, third, and fourth RBF kernel applied to first data from the domain matrix in the first partition, second data from the domain matrix in the second partition, and third data from the domain matrix in the third partition of the matrix and a second set of one or more length-scale parameters; representing the second, third and fourth covariance terms as a second, third, and fourth Kronecker product; calculating a second maximum likelihood for the alternative model; calculating a difference between the first maximum likelihood for the null model and the second maximum likelihood for the alternative model; calculating a test statistic based at least in part on the difference; and identifying existence of the correlation between the SNP and the function-valued trait based at least in part on the test statistic.