Preliminary exploration of time course DNA microarray data with correlation maps

In the analysis of data from high-throughput experiments, information regarding the underlying data structure provides the researcher with confidence in the appropriateness of various analysis methods. One extremely simple but powerful data visualization method is the correlation heat map, whereby correlations between experiments/conditions are calculated and represented using color. In this work, the use of correlation maps to shed light on transcription patterns from DNA microarray time course data prior to gene-level analysis is described. Using three different time course studies from the literature, it is shown how the patterns observed at the array level provide insights into the dynamics of the system under study and the experimental design.