Becton, Dickinson and Company
Method for Optimal Scaling of Cytometry Data for Machine Learning Analysis and Systems for Same

Abstract:

Aspects of the present disclosure include methods for processing and scaling cytometric data. Methods according to certain embodiments include obtaining cytometric data for a sample, wherein the cytometric data comprises measurements of a plurality of parameters from particles irradiated in the sample flowing in a flow stream; identifying a parameter of interest; specifying positive and negative measurement intervals on the parameter of interest; scaling the cytometric data by transforming the parameter of interest based at least in part on the corresponding specified positive and negative intervals. Systems for practicing the subject methods are also provided. Non-transitory computer readable storage mediums are also described.