Tiling arrays are useful for exploring local functions of regions of the genome in an unbiased fashion. The exact determination of those genomic regions based on tiling-array data, e.g., generated by means of hybridization with immunopreciptated DNA-fragments to the arrays is a challenge. Many different statistical methodologies have been developed to find biological relevant regions-of-interest (ROI) by using the quantitative signal intensity of each probe. We previously developed a method called Hypergeometric Analysis of Tiling arrays (HAT) for the analysis of tiling-array data, but it is developed such that it can also be used to study data derived by genome-wide deep sequencing approaches. Here we applied HAT to analyze two publicly available tiling-array data sets. After the detection of statistically significant ROI, these are often used in additional analysis for hypothesis testing. We therefore discuss, by using the results of the tiling-array experiment, pathway and motif analyses.