Baylor College of Medicine and Golden Helix have entered into collaboration to introduce the Combined Multivariate and Collapsing (CMC) and the Kernel Based Adaptive Cluster (KBAC) methods in Golden Helix's product SNP & Variation Suite (SVS).
SVS is an integrated collection of analytic tools for managing, analyzing and visualizing large-scale, complex genomic data.
CMC and KBAC, developed under the direction of Baylor’s Department of Molecular and Human Genetics professor Suzanne Leal, are methods of analyzing rare DNA sequence variants.
Golden Helix and Baylor worked together to create a version that leverages a regression framework.
The regression-based adaptations allow users to correct for confounding variables that might otherwise result in spurious results.
Golden Helix president and CEO Christophe Lambert said the standard methods to analyze common variants in GWAS data are used to test rare variant complex trait associations.