Workflow for image-based screening, image quantification and phenotypic dissimilarity measure with SVM classification accuracy. A) Cells are seeded into 384-well plates and treated with siRNA by reverse transfection. After incubation for 48 hours, cells are fixed, permeabilized and immunostained for DNA, tubulin and actin and imaged with an automated microscope. B) Cell images are processed with nucleus and cell segmentation using the R packages EBImage and imageHTS. Each cell is represented by a 46 image-based feature vector. Every treatment generates a data matrix X[m,n], where m is the number of cells and n is the number of features. C) For each pair of RNAi treatments, SVM classification is performed on the virtually pooled cell population based on cell features. Classification accuracy is estimated by cross validation, and defined as the phenotypic dissimilarity between treatments.