knitr::opts_chunk$set(echo = TRUE, cache = FALSE, eval = TRUE,
                      warning = TRUE, message = TRUE)


Dear flowSpy users:

To improve the identification of this package and avoid awkward duplication of names in some situations, we decided to change the name of flowSpy to CytoTree. The package name of CytoTree more fits the functional orientation of this software. The usage and update of flowSpy and CytoTree will be consistent until the end of Bioc 3.11. And for the 3.12 devel, flowSpy will be deprecated.

The package CytoTree has been added to Bioconductor (, we recommend that users can download this package and replace flowSpy as soon as possible.

We apologized for the inconvenience.

flowSpy team



Although multidimensional single-cell-based flow and mass cytometry have been increasingly applied to microenvironmental composition and stem-cell research, integrated analysis workflows to facilitate the interpretation of experimental cytometry data remain underdeveloped. We present flowSpy, a comprehensive R package designed for the analysis and interpretation of flow and mass cytometry data. We applied flowSpy to mass cytometry and time-course flow cytometry data to demonstrate the usage and practical utility of its computational modules. flowSpy is a reliable tool for multidimensional cytometry data workflows and produces compelling results for trajectory construction and pseudotime estimation.

Overview of flowSpy workflow

The flowSpy package is developed to complete the majority of standard analysis and visualization workflow for FCS data. In flowSpy workflow, an S4 object in R is built to implement the statistical and computational approach, and all computational modules are integrated into one single channel which only requires a specified input data format.

flowSpy can help you to perform four main types of analysis:

Workflow of flowSpy
Fig. 1 Workflow of flowSpy


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