Canonical correlation analysis (CCA) can be used to capture the underlying genetic background of a complex disease, by associating two datasets containing information about a patients phenotypical and genetic details. Often the genetic information is measured on a qualitative scale, consequently ordinary CCA cannot be applied to such data. Moreover, the size of the data in genetic studies can be enormous, thereby making the results difficult to interpret.