Introduction: The information content of multiparametric flow cytometry experiments is routinely underexploited given the paucity of adequate tools for unbiased comprehensive data analysis that can be applied successfully and independently by immunologists without computational training.
Methods: We aimed to develop a tool that allows straightforward access to the entire information content of any given flow cytometry panel for immunologists without special computational expertise. We used a data analysis approach which accounts for all mathematically possible combinations of markers in a given panel, coded the algorithm and applied the method to mined and self-generated data sets.
Results: We developed Flow Plex, a straightforward computational tool that allows unrestricted access to the information content of a given flow cytometry panel, enables classification of human samples according to distinct immune phenotypes, such as different forms of autoimmune uveitis, acute myeloid leukemia vs "healthy", "old" vs "young", and facilitates the identification of cell populations with potential biologic relevance to states of disease and health.
Conclusions: We provide a tool that allows immunologists and other flow cytometry users with limited bioinformatics skills to extract comprehensive, unbiased information from flow cytometry data sets.
Keywords: computation; data analysis; flow cytometry.
© 2019 The Authors. Immunity, Inflammation and Disease Published by John Wiley & Sons Ltd.