Dual Analysis of DNA Microarrays

Microarray data represents the expression levels of genes for differ-ent samples and for different conditions. It has been a central topic in bioinformatics research for a long time already. Researchers try to discover groups of genes that are responsible for specific bio-logical processes. Statistical analysis tools and visualizations have been widely used in the analysis of microarray data. Researchers try to build hypotheses on both the genes and the samples. There-fore, such analyses require the joint exploration of the genes and the samples. However, current methods in interactive visual analysis fail to provide the necessary mechanisms for this joint analysis. In this paper, we propose an interactive visual analysis framework that enables the dual analysis of the samples and the genes through the use of integrated statistical tools. We introduce a set of specialized views and a detailed analysis procedure to describe the utilization of our framework