The present investigation includes some of the largest sample sizes that are currently available for a relatively homogeneous outbred macaque colony. Nevertheless, the numbers of animals represented in the datasets used for this study are quite small relative to those used for performing association studies in human populations. For this reason, we neither have the power to perform refined haplotype analysis nor can we examine complex interactive effects with other functional genetic variants (i.e., HTT-LPR, MAOA-LPR, OPRM1 C77G) that may be contributing to the variance in our phenotypes of interest. We have elected to use an approach that relies on cladistic clustering of haplotypes and functional characterization of variants in order to determine whether genetic variation is associated with our phenotypes of interest, using factor analysis to generate behavioral clusters so that the number of statistical comparisons is minimized. Experimental studies in humans as well as non-human primates 16, 37, 57, 58 have repeatedly demonstrated the gain in power that comes from designs that genotype a relatively small number of subjects for functional genetic variation, measure fine-grained, quantitative phenotypic traits,
