In patients with age-related macular degeneration, a monolayer of cells in the eyes called retinal pigment epithelium differ from healthy ones in morphology. It is therefore important to quantify the morphological changes, which will help us better understand the physiology, disease progression and classification. Classification of the RPE morphometry has been accomplished with whole tissue data. In this work, we focused on the spatial aspect of RPE morphometric analysis. We used the second-order spatial analysis to reveal the distinct patterns of cell clustering between normal and diseased eyes for both simulated and experimental human RPE data. We classified the mouse genotype and age by the k-Nearest Neighbors algorithm. Radially aligned regions showed different classification power for several cell shape variables. Our proposed methods provide a useful addition to classification and prognosis of eye disease noninvasively.