Combining genotype groups and recursive partitioning: an application to human immunodeficiency virus type 1 genetics data

Understanding the relationship between human immunodeficiency virus type 1 genotypic markers of resistance and response to therapy presents an analytic challenge because of the high dimensionality of the viral genome and the complex interactions across sites on the genome. Recursive partitioning is a natural approach to classifying patients on the basis of covariates that capture information on the variability of a response variable and is therefore well suited to handling both of these features of the problem. In the human immunodeficiency virus genetics setting, we aim to classify patients on the basis of the genotypic characteristics of their infecting viral population so that the resulting groups explain the most variability in drug susceptibility phenotype. Recursive partitioning is also informative in identifying meaningful genotypic patterns that define the resulting classes. By combining dimension reduction techniques with recursive partitioning we can arrive at different classification schemes which are potentially more informative. Furthermore, the use of weighted distance metrics in the clustering algorithm allows us to update and potentially to improve on this classification scheme. An illustration of the relative benefits of the various approaches is provided by using 2559 protease sequences and the corresponding 50% inhibitory concentrations for Indinavir.