Methods, systems, and apparatuses for quantitative analysis of heterogeneous biomarker distribution

A method of characterizing heterogeneity in a cell sample comprising one or more analytes labeled with a detectable marker, the method comprising analyzing an image of the cell sample on a computer apparatus comprising a computer processor programmed to apply a cluster analysis to a dataset obtained from the image of the cell sample to create a cluster map comprising a plurality of clusters of expression patterns, wherein:

• (a) the dataset comprises an image stack for at least a portion of the image of the cell sample, wherein the image stack comprises a x-axis, a y-axis, and a z-axis, wherein the x-axis and the y-axis represent spatial coordinates within the portion of the image, and the z-axis comprises a number of ‘n’ layers, wherein each layer of the z axis comprises intensity data for a single detectable marker at a plurality of x,y coordinates;
• (b) the cluster analysis comprises applying an unsupervised, non-parametric, density-based clustering algorithm to the image stack, wherein the clustering algorithm clusters points (defined by the dataset in an at least n+2 dimensional space, where each point is given by x,y coordinates and ‘n’ intensity data values from the n layers at the respective x,y coordinate in the image stack, thereby generating the plurality of clusters,
• (c) outputting of output data being representative of the result of the cluster analysis, the data being indicative of the heterogeneity in the cell sample, wherein the image is a multi-channel image and wherein the ‘n’ layers are obtained by unmixing the multi-channel image.