Applications of resampling methods

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This research program will look at three areas of application for resampling-based methodologies. The first is to the analysis of gene expression data arising from designed experiments and in particular to the search for gene-environment interactions. These interactions are widely hypothesized to exist in many complex diseases. Finding these interactions at a gene-expression level, however has not been easy. Standard parametric tests are not generally useful in this setting but permutation and resampling based methods can be used. Most analyses of microarrays does not take into account the dependence between genes for a single individual. There is a lot of information about gene function and relationships available, however. I will examine how we can incorporate this information into the anlysis. I will also look at ways to take genetic information into account in dealing with the multiple testing problem and estimating the false discover rate.