The invention relates to a method for classifying selected marker signals from cytometric measurements comprising a first measurement and a second measurement, wherein the first measurement comprises a cytometric measurement acquired from a first sample of particles, and the second measurement comprises a cytometric measurement acquired from a second sample of N2 particles, being the number of particles in the first sample and N2 being the number of particles in the second sample. Each particle njN 1 of the N1 particles of the first sample is labelled with a number of L1 fluorescent, mass or oligo markers ljN 1. Each particle n1N 2 of the N2 particles of second sample is labelled with a number of L2 fluorescent, mass or oligo markers ljN2′ With the acquired data a machine learning method is trained such that the marker combinations showing the most significant differences for two distinct populations are selected and displayed to a user in a novel fashion.