Automated Quadratic Characterization of Flow Cytometer Instrument Sensitivity

Flow cytometer sensitivity has been well defined in the community and relates to two functions: (1) How well a dim staining population is resolved from an unstained population; (2) How well various dim staining populations can be distinguished from each other. The most common terms for characterizing flow cytometer sensitivity are known as Q (detector efficiency) and B (background light level), which are calculated using beads acquired on a cytometer. Any routine method to measure Q and B must be rapid and sufficiently accurate to provide useful results, see the works in [1, 2, 3]. Manually gating multi-peak bead data to generate the MFIs and SDs from the beads is an extremely time-consuming process. We showed the feasibility of an automated approach based on the clustering algorithm Kmeans to detect the bead sub-populations and to generate the MFIs and SDs in an easy and fully automatic rapid fashion. Furthermore, we extended the standard linear formulation, used to derive coefficients for Q and B calculation, with a quadratic term that is taking into account intrinsic variance from both the instrument and the bead product, see the work in [4]. Consequently we have developed a fully automated R Bioconductor package that we call flowQB. This document is intended to provide full access to