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Modern genetic epidemiology faces the challenge of dealing with hundreds of thousands of genetic markers. The selection of a small initial subset of interesting markers for further investigation can greatly facilitate genetic studies. In this contribution we suggest the use of a logistic regression tree algorithm known as logistic tree with unbiased selection. Using the simulated data provided for Genetic Analysis Workshop 15, we show how this algorithm, with incorporation of multifactor dimensionality reduction method, can reduce an initial large pool of markers to a small set that includes the interesting markers with high probability.

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Males may share access to fertilizable females (polygynandry) in one environment while, under other conditions, polygynous (one-male or 'harem') mating is the norm. However, few studies in mammals have empirically investigated the factors predicting when males will coexist in bisexual reproductive units rather than live in one-male associations with females. We examined patterns of male group membership in a population of black howler monkeys Alouatta pigra residing in two habitats (deciduous and riparian) of a tropical moist forest environment in Belize, Central America. Using general linear and logistic regression modeling, we evaluated nine variables as possible predictors of male residence patterns (onemale groups or multimale groups). Our results suggest that adult sex ratio and group size are the best predictors of male residence patterns in both habitats. Our findings provide empirical support for theoretical expectations that male reproductive strategies will be a function of habitat-related demographic patterns and the subsequently varying potential of males to monopolize females in heterogeneous regimes. This study may have important implications for our understanding of features of mammalian societies in which males compete directly for access to females.

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