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METHODS FOR IDENTIFYING CLUSTERS IN A DATASET, METHODS OF ANALYZING CYTOMETRY DATA WITH THE AID OF A COMPUTER AND METHODS OF DETECTING CELL SUB-POPULATIONS IN A PLURALITY OF CELLS
METHODS FOR IDENTIFYING CLUSTERS IN A DATASET, METHODS OF ANALYZING CYTOMETRY DATA WITH THE AID OF A COMPUTER AND METHODS OF DETECTING CELL SUB-POPULATIONS IN A PLURALITY OF CELLS
According to various embodiments, there is provided a method for identifying clusters in a dataset, the method including: determining for each data point in the dataset, a plurality of parameters including a first parameter and a second parameter, the first parameter being a distance between the data point and a nearest other data point having a local density that is higher than a local density of the data point, and the second parameter being a function of the local density of the data point and the first parameter; running statistical tests on each of the first parameter and the second parameter across the dataset, to identify outliers of the first parameter and outliers of the second parameter; and designating each data point where both the first parameter and the second parameter are identified outliers, as a centre of a respective cluster.
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