Systems biology approach for gene set enrichment and topological analysis of Alzheimer's disease pathway

Abstract

Deciphering the underlying mechanisms of all complex interactions involved in different signaling pathways is a pivotal step in the dissection and study of network-based data. Heuristic statistical solutions are conventionally used across the world to derive a meaningful perspective of the network based data by identifying related biological networks. However, classical pathway analysis gives us elusive results by ignoring important aspects of biology. To overcome the limitations of the classical analysis, we have implemented systems biology approach which includes enrichment analysis of Alzheimer's disease (AD) gene set and topological enrichment analysis. Exploration of pathway ranking and regression analysis on the basis of XD-Score and Fisher-q value is also elucidated. Topology-based enrichment studies gave us insight on important parameters such as shortest path length, node betweenness, degree, clustering coefficient, eigenvector centrality and their association in AD based statistical score which turned out to be significantly high (5.062) at a significant threshold (0.74). A linear fit in regression plot and enrichment in associated gene pathways were observed.