Quick start of flowSpy

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


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. Computational modules of flowSpy can be divided into four main parts (Fig. 1): preprocessing, trajectory, analysis and visualization.

Workflow of flowSpy

Fig. 1. Workflow of flowSpy

A PDF version of the instructions and standard workflow can be found at:

Use cases could be found at:


And PDF version of the specific workflows for flow and mass cytometry data can be found at:


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flowSpy documentation built on Nov. 8, 2020, 6:53 p.m.