Cell membrane proteins play an important role in tissue architecture and cell-cell communication. We hypothesize that segmentation and multivariate characterization of the distribution of cell membrane proteins, on a cell-cell basis, enable improved classification of treatment groups and identify important characteristics that can otherwise be hidden. We have developed a series of computational steps to (i) delineate cell membrane protein signals and associate them with specific nuclei, (ii) compute a coupled representation of the multiplexed DNA content with membrane proteins and other end points, (iii) rank computed features associated with such a multivariate representation, (iv) visualize selected features for comparative evaluation, and (v) discriminate between treatment groups in an optimal fashion. The novelty of our method is in the segmentation of the membrane signal and the multivariate representation of phenotypes on a cell-cell basis. To test the utility of the new method,...
Ju Han, Hang Chang, Kumari L. Andarawewa, Paul Yas