However, the use of polychromatic flow cytometry requires proper analytical software to analyze these highly complex datasets. These improvements have allowed for synchronized identification of numerous immune system components, including lineage and functional markers of leukocytes, which have significant implications in understanding basic biologic behavior, immune monitoring techniques, and immunotherapy design. Further development and awareness of available tools will help guide proper data analysis to answer difficult biologic questions arising from incredibly complex datasets.Īdvancement in flow cytometry instrumentation and reagent development has lifted the ceiling for the analysis of large numbers of cellular parameters. This detailed approach may serve as a model for other investigators/SRLs in selecting the most appropriate software to analyze complex flow cytometry datasets. Of the tools investigated, automated classification of cellular expression by nonlinear stochastic embedding (ACCENSE) and coupled analysis in Pestle/simplified presentation of incredibly complex evaluations (SPICE) provided the most user‐friendly manipulations and readable output, evaluating effects of altered antigen‐specific stimulation on T cell polyfunctionality. Various software packages were used, analysis methods used in each described, and representative output displayed. Analysis of 7 parameters resulted in 128 possible combinations of positivity/negativity, far too complex for basic flow cytometry software to analyze fully. We assessed polyfunctional potential of TCR‐transduced T cells, serving as a model evaluation, using multidimensional flow cytometry to analyze 6 intracellular cytokines and degranulation on a per‐cell basis. Here, we comparatively assess various multidimensional flow cytometry software packages for their ability to answer a specific biologic question and provide graphical representation output suitable for publication, as well as their ease of use and cost.

A problem among many investigators and flow cytometry Shared Resource Laboratories (SRLs), including our own, is a lack of access to a flow cytometry‐knowledgeable bioinformatics team, making it difficult to learn and choose appropriate analysis tool(s). Highly complex datasets generated by polychromatic flow cytometry require proper analytical software to answer investigators’ questions. Advancement in flow cytometry reagents and instrumentation has allowed for simultaneous analysis of large numbers of lineage/functional immune cell markers.

Boolean gating in flowjo 10