Abstract
There has been a continuing interest in approaches that analyze pairwise locus-by-locus (epistasis) interactions using multilocus association models in genome-wide data sets. In this paper, we suggest an approach that uses sure independence screening to first lower the dimension of the problem by considering the marginal importance of each interaction term within the huge loop. Subsequent multilocus association steps are executed using an extended Bayesian least absolute shrinkage and selection operator (LASSO) model and fast generalized expectation-maximization estimation algorithms. The potential of this approach is illustrated and compared with PLINK software using data examples where phenotypes have been simulated conditionally on marker data from the Quantitative Trait Loci Mapping and Marker Assisted Selection (QTLMAS) Workshop 2008 and real pig data sets.
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