Genome-wide association studies have typically been analyzed with univariate statistical methods, which do not reflect the multi-locus genetic background of complex, quantitative traits. Block, Pass, Score is a multivariate analysis methodology developed to produce models that better reflect the multiple loci that are relevant for complex, quantitative traits. Investigation of interaction terms is introduced as part of the methodology. Block, Pass, Score performs better than the standard univariate approach, locating more relevant genomic areas and producing models that explain more of the trait variation.