A method of computing inter-marker heterogeneity scores for a biological sample having a plurality of stains, the method comprising: (i) extracting features from a first image having a first stain, the extracted features used to classify cells within the first image; (ii) identifying one or more clusters of cells within the first image by applying a cell classification to the extracted features of the first image, the one or more clusters of cells identified by using a graph theoretic approach; (iii) registering the first image and at least one additional image to a common coordinate system such that the identified one or more clusters of cells in the first image are mapped to the at least one additional image to provide mapped clusters of cells, where the at least one additional image comprises a different stain; (iv) detecting and classifying cells of the mapped one or more clusters of cells in the at least one additional image; (v) deriving expression scores for each stain in each of the one or more clusters of cells in the first image and in each of the mapped one or more clusters of cells in the at least one additional image; and (vi) computing, based on the derived expression scores, one or more inter-marker heterogeneity scores, wherein an inter-marker heterogeneity score of the one or more inter-marker heterogeneity scores identifies, for a corresponding biomarker that is a particular type of protein or peptide, a difference of protein or peptide expression levels for the particular protein or peptide type between the one or more clusters of cells within the first image and the mapped one or more clusters of cells within the at least one additional image. (i) extracting features from a first image having a first stain, the extracted features used to classify cells within the first image; (ii) identifying one or more clusters of cells within the first image by applying a cell classification to the extracted features of the first image, the one or more clusters of cells identified by using a graph theoretic approach; (iii) registering the first image and at least one additional image to a common coordinate system such that the identified one or more clusters of cells in the first image are mapped to the at least one additional image to provide mapped clusters of cells, where the at least one additional image comprises a different stain; (iv) detecting and classifying cells of the mapped one or more clusters of cells in the at least one additional image; (v) deriving expression scores for each stain in each of the one or more clusters of cells in the first image and in each of the mapped one or more clusters of cells in the at least one additional image; and (vi) computing, based on the derived expression scores, one or more inter-marker heterogeneity scores, wherein an inter-marker heterogeneity score of the one or more inter-marker heterogeneity scores identifies, for a corresponding biomarker that is a particular type of protein or peptide, a difference of protein or peptide expression levels for the particular protein or peptide type between the one or more clusters of cells within the first image and the mapped one or more clusters of cells within the at least one additional image. <EOS>