
Flow Plex —A tool for unbiased comprehensive flow cytometry data analysis
Author(s) -
Nowatzky Johannes,
Resnick Ezra,
Manasson Julia,
Stagnar Cristy,
AlObeidi Arshed Fahad,
Manches Olivier
Publication year - 2019
Publication title -
immunity, inflammation and disease
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.918
H-Index - 18
ISSN - 2050-4527
DOI - 10.1002/iid3.246
Subject(s) - flow cytometry , computer science , relevance (law) , identification (biology) , flow (mathematics) , computational biology , information flow , cytometry , data mining , medicine , immunology , biology , mathematics , linguistics , philosophy , botany , geometry , political science , law
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.