knitr::opts_chunk$set(echo = TRUE, cache = FALSE, eval = TRUE,
                      warning = TRUE, message = TRUE,
                      fig.width = 6, fig.height = 5)

Introduction

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 CytoTree, a comprehensive R package designed for the analysis and interpretation of flow and mass cytometry data. We applied CytoTree to mass cytometry and time-course flow cytometry data to demonstrate the usage and practical utility of its computational modules. CytoTree is a reliable tool for multidimensional cytometry data workflows and produces compelling results for trajectory construction and pseudotime estimation.

Overview of CytoTree workflow

The CytoTree package is developed to complete the majority of standard analysis and visualization workflow for FCS data. In CytoTree 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.

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

Workflow of CytoTree
Fig. 1 Workflow of CytoTree

Quick start

## 2021-05-19 17:27:50 Number of cells in processing: 600
## 2021-05-19 17:27:50 rownames of meta.data and raw.data will be named using column cell
## 2021-05-19 17:27:50 Index of markers in processing
## 2021-05-19 17:27:50 Creating CYT object.
## 2021-05-19 17:27:50 Determining normalization factors
## 2021-05-19 17:27:50 Normalization and log-transformation.
## 2021-05-19 17:27:50 Build CYT object succeed
## CYT Information:
##  Input cell number: 600  cells 
##  Enroll marker number: 10  markers 
##  Cells after downsampling: 600  cells
## Mapping data to SOM
## 2021-05-19 17:27:55 Calculating Pseudotime.
## 2021-05-19 17:27:55 Pseudotime exists in meta.data, it will be replaced.
## 2021-05-19 17:27:55 The log data will be used to calculate pseudotime
## 2021-05-19 17:27:55 Calculating Pseudotime completed.
## 2021-05-19 17:27:55 37 cells will be added to leaf.cells .
## 2021-05-19 17:27:55 Calculating walk between root.cells and leaf.cells .
## 2021-05-19 17:27:55 Generating an adjacency matrix.
## 2021-05-19 17:27:55 Walk forward.
## 2021-05-19 17:27:55 Calculating walk completed.

## Warning: `fun.y` is deprecated. Use `fun` instead.

## Warning: `fun.y` is deprecated. Use `fun` instead.

## Warning: `fun.y` is deprecated. Use `fun` instead.

## `geom_smooth()` using formula 'y ~ x'

Announcement

The previous version of CytoTree is flowSpy link to GitHub and link to Bioconductor. To improve the identification and avoid awkward duplication of names in some situations, we changed the name of flowSpy to CytoTree. CytoTree more fits the functional orientation of this software.

We apologized for the inconvenience.

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