Background: Combining diverse data streams across different levels of biological observation, such as molecular, cellular, and clinical chemistry responses, support a system-wide diagnostic approach. Recent progress in slide-based cytometry contributes to the development of tissomics, a high-throughput and high-content phenotyping methodology that provides data-rich profiles of cellular heterogeneity in tissues enabling correlative statistical treatments over multiple scales of biological hierarchies.
Methods: Phenotypical data are covariants that can be used as biomarkers to identify relevant candidate genes by associating initiating molecular events with phenotypical changes and adverse outcomes. We introduce a procedure of combined statistical and analytical tools to identify and visualize such associations for nonpooled entities. The new utility is applied to a time-controlled, low-dose toxicological study including a control and two xenobiotic compounds.
Results: An integrated analysis identified specific molecular and phenotypical biomarkers, which support the classification of animals in the absence of any visual indicators from pathology readings.
Discussion: The introduction of controlled perturbations to tissues provides a prototypical setting to develop a sensitive, systems-based analysis methodology suitable for a broader range of biomedical applications.