Detecting Locus-Locus Interactions Using Microarray Data

Abstract

In this report we explore how to find the locus-locus interaction using microarray data. Our analysis makes use of a dataset from an experiment with Affymetrix GeneChip MGU74Av2 for mice. In Chapter 1 we give the genetics background, an introduction to microarray methodology and the preprocessing of microarray data, and a review of SAM (Significance Analysis of Microarrays) method for finding differentially expressed genes in microarray data. In Chapter 2 we describe our dataset and our objective of finding the genes with locus-locus interaction but with no main effect. We also show how to find the interaction in this chapter. In Chapter 3 we show the simulation study of detecting the locus-locus interaction without main effects and propose a two-stage method of doing that. In Chapter 4 we apply the two-stage method to the microarray data and focus on the second stage analysis. In Chapter 5 we examine an alternative method using bootstrap resampling in place of permutations. Chapter 6 contains our conclusion and some suggestions for future research.