Figure 3.

Analyzing cell covariance and creating raster layers

(A) Tessellation of NeuN cells showing regions of low and high neuronal numbers. The quadrantcount function enables the user to estimate the number of covariate cells (in this case GFAP).

(B) Rhohat functions enable the user to estimate the spatial covariance between the cells of interest at different spatial intensity and distance scales.

(C) The raster function produces a set of raster layers as a pixel image that allows the user to separate regions based on the spatial intensity of cells.

(D) The isolated regions can be analyzed independently.