Systems and methods for identifying populations of events in a
multi-dimensional data set are described. The populations may, for
example, be sets or clusters of data representing different white blood
cell components in sample processed by a flow cytometer. The methods use
a library consisting of one or more one finite mixture models, each model
representing multi-dimensional Gaussian probability distributions with a
density function for each population of events expected in the data set.
The methods further use an expert knowledge set including one or more
data transformations and one or more logical statements. The
transformations and logical statements encode a priori expectations as to
the populations of events in the data set. The methods further use
program code by which a computer may operate on the data, a finite
mixture model selected from the library, and the expert knowledge set to
thereby identify populations of events in the data set.