Aspergillus flavus is a pathogenic fungus infecting maize and producing aflatoxins that are health hazards to humans and animals. Characterizing host defense mechanism and prioritizing candidate resistance genes are important to the development of resistant maize germplasm. We investigated methods amenable for the analysis of the significance and relations among maize candidate genes based on the empirical gene expression data obtained by RT-qPCR technique from maize inbred lines. We optimized a pipeline of analysis tools chosen from various programs to provide rigorous statistical analysis and state of the art data visualization. A network-based method was also explored to construct the empirical gene expression relational structures. Maize genes at the centers in the network were considered as important candidate genes for maize DNA marker studies. The methods in this research can be used to analyze large RT-qPCR datasets and establish complex empirical gene relational structures across multiple experimental conditions.