Abstract: Methods for detecting heterogeneity in data (e.g., flow cytometer data, nucleic acid sequence data) are provided. In some instances, methods include generating one or more population clusters based on the determined parameters of the analytes (e.g., cells, particles, nucleic acids) in a biological sample sample. In embodiments, methods include calculating a resolution index by computing a ratio between measures of variability and separation distance for any given number of pairs of first and second populations of data. Where desired, methods also include maximizing the resolution between populations of data by computing a resolution score that accounts for the sum of resolution indices, the number of populations, the number of parameters and the number of cells. Systems and computer-readable media for determining heterogeneity between populations of data and, where desired, maximizing resolution between populations of data, are also provided.