Phenotyping genetic diseases using an extension of mu-scores for multivariate data

As the field of genomics matures, more complex genotypes and phenotypes are being studied. Fanconi anemia (FA), for example, is an inherited chromosome instability syndrome with a complex array of variable disease phenotypes including congenital malformations, hematological manifestations, and cancer. To better understand specific aspects of the genetic etiology of FA and other rare diseases with complex phenotypes, it is often necessary to reduce the dimensions of the disease phenotype information. Towards this end, we extend a novel non-parametric approach to include information about a hierarchical structure among disease phenotypes. The proposed extension increases information content of the phenotype scores obtained and, thereby, the power of genotype-phenotype relationships studies.