Improved compensation in flow cytometry by multivariable optimization

Abstract

Conventional compensation of flow cytometry (FMC) data of an N-stained sample requires additional data sets, of N single-stained control samples, to estimate the spillover coefficients. Single-stained controls however are the least rigorous controls because any of the multi-stained controls are closer to the N-stained sample. In this article, a new, optimization based, compensation method has been developed that is able to use not only single- but also multi-stained controls to improve estimates of the spillover coefficients. The method is demonstrated on a data set from five-stained dentritic cells (DCs) with five single-stained and eight multi-stained controls. This approach is practical and leads to significant improvements in FCM compensation.