Alzheimer's disease is a complex neurodegenerative disease whose basic etiology and genetic structure remains elusive, despite decades of intensive investigation. To date, the significant genetic markers identified have no obvious functional effects, and are unlikely to play a role in Alzheimer's disease etiology, themselves. These markers are likely linked to other genetic variations, rare or common. Regardless of what causal mutations are found, research has demonstrated that no single gene determines Alzheimer's disease development and progression. It is clear that Alzheimer's disease development and progression are based on a set of interactions between genes and environmental variables. This dissertation focuses on gene-gene interactions (epistasis) and their effects on Alzheimer's disease case-control status. We genotyped the top Alzheimer's disease genetic markers as found on AlzGene.org (accessed 2014), and tested for interactions that were associated with Alzheimer's disease case- control status. We identified two potential gene-gene interactions between rs11136000 (CLU) and rs670139 (MS4A4E) (synergy factor = 3.81; p = 0.016), and rs3865444 (CD33) and rs670139 (MS4A4E) (synergy factor = 5.31; p = 0.003). Based on one data set alone, however, it is difficult to know whether the interactions are real. We replicated the CLU-MS4A4E interaction in an independent data set from the Alzheimer's Disease Genetics Consortium (synergy factor = 2.37, p = 0.007) using a meta-analysis. We also identified potential dosage (synergy factor = 2.98, p = 0.05) and APOE ε4 effects (synergy factor = 4.75, p = 0.005) in Cache County that did not replicate independently. The APOE ε4 effect is an association with Alzheimer's disease case-control status in APOE ε4 negative individuals. There is minor evidence both the dosage (synergy factor = 1.73, p = 0.02) and APOE ε4 (synergy factor = 2.08, p = 0.004) effects are real, however, because they replicate when including the Cache County data in the meta-analysis. These results demonstrate the importance of understanding the role of epistasis in Alzheimer's disease. During this research, we also developed a novel tool known as the Variant Tool Chest. The Variant Tool Chest has played an integral part in this research and other projects, and was developed to fill numerous gaps in next-generation sequence data analysis. Critical features include advanced, genotype-aware set operations on single- or multi-sample variant call format (VCF) files. These features are critical for genetics studies using next-generation sequencing data, and were used to perform important analyses in the third study of this dissertation.By understanding the role of epistasis in Alzheimer's disease, researchers will begin to untangle the complex nature of Alzheimer's disease etiology. With this information, therapies and diagnostics will be possible, alleviating millions of patients, their families and caregivers of the painful experience Alzheimer's disease inflicts upon them.