1. An automated reader for reading fluorescence in-situ hybridization signals, comprising: one or more computer processors for receiving a digitized FISH image comprising a plurality of spots having colors, wherein the one or more processors being are programmed to execute the steps of: converting colors within the FISH image to a hue value; separately for each color: extracting a plurality of quantitative values to detect the presence of signals corresponding to spots; and applying a plurality of algorithms to extract features from the signals to determine cell shapes and segment cells within the FISH image; recombining the extracted features for the colors; using a first learning machine and a first subset of the extracted features, classifying the plurality of spots according to the color of each spot to generate spot classifications, wherein at least of portion of said spot classifications are associated with close proximity or partially overlapping spots within the FISH image and comprise merged signals; using a second learning machine and a second subset of the extracted features, separating said merged signals to generate separated spot classifications; counting said spot classifications and said separated spot classifications to determine relative frequency of colors among the plurality of spots; and generating a report of the number of classified spots of each color.