Introduction: Existing methods such as correlation plots and cluster heat maps are insufficient in the visual exploration of multiple associations between genetics and phenotype, which is of importance to achieve a better understanding of the pathophysiology of psychiatric and other illnesses. The implementation of a combined presentation of effect size and statistical significance in a graphical method, added to the ordering of the variables based on the effect-ordered data display principle was deemed useful by the authors to facilitate in the process of recognizing meaningful patterns in these associations. Materials and methods: The requirements, analyses and graphical presentation of the feature-expression heat map are described. The graphs display associations of two sets of ordered variables where a one-way direction is assumed. The associations are depicted as circles representing a combination of effect size (color) and statistical significance (radius). Results: An example dataset is presented and relation to other methods, limitations, areas of application and possible future enhancements are discussed. Conclusion: The feature-expression heat map is a useful graphical instrument to explore associations in complex biological systems where one-way direction is assumed, such as genotype-phenotype pathophysiological models.

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Journal of Biomedical Informatics
Erasmus MC: University Medical Center Rotterdam

Haarman, B., Riemersma-Van der Lek, R., Nolen, W., Mendes, R., Drexhage, H., & Burger, H. (2015). Feature-expression heat maps - A new visual method to explore complex associations between two variable sets. Journal of Biomedical Informatics, 53, 156–161. doi:10.1016/j.jbi.2014.10.003