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Abstract
The ability to distinguish organizational patterns of cells is essential for understanding organ maintenance and function; however, statistical methods for quantifying cellular organization do not exist. The development of techniques to quantitatively identify recurrent or cryptic cellular patterns could help us to better understand healthy tissue states, and would allow us to make comparisons with tissues in states of disequilibrium. Here, we have developed novel computational analyses that allow us to study the organ of our choice, the thymus, in a purely statistical framework. We accomplish this by borrowing techniques commonly used in ecology and applying them to the thymus; we are able to make this comparison due to the remarkable similarities in behavior and function exhibited by both cell types in organs and species in ecological communities. The output generated from these analyses can be used to better understand healthy thymic homeostasis and states of disequilibrium.