CytoRSuite: Manual and Automated Gating

Dillon Hammill

2019-03-07

1. Overview

CytoRSuite is built on and shares the same gatingTemplate as the openCyto package. This means that users can take advantage of both the manual gating in CytoRSuite and the automated gating in openCyto for their analyses. Furthermore, CytoRSuite users can take advantage of some of the other features of the openCyto gatingTemplate, such as boolean and reference gates. More information on the openCyto gatingTemplate can be found here.

2. Demonstration

Here we aim to demonstrate the use of both manual and automated gating approaches using CytoRSuite and openCyto. For demonstration purposes we will use the Activation dataset shipped with CytoRSuiteData.

2.1 Preparation of Activation Dataset for Gating

library(CytoRSuite) # openCyto is imported with CytoRSuite
library(CytoRSuiteData)

# Assign Activation flowSet to fs
fs <- Activation

# Add fs to a GatingSet
gs <- GatingSet(fs)

# Apply compensation
gs <- compensate(gs, fs[[1]]@description$SPILL)

# Transform fluorescent channels
trans <- estimateLogicle(gs[[4]], cyto_fluor_channels(gs))
gs <- transform(gs, trans)

2.2 Manually Gate Cells

# gate_draw returns gatingTemplate entry
template <- gate_draw(gs,
                      parent = "root",
                      alias = "Cells",
                      channels = c("FSC-A","SSC-A"))

2.3 Manually Gate Single Cells

template <- rbind(template, gate_draw(gs,
                                      parent = "Cells",
                                      alias = "Single Cells",
                                      channels = c("FSC-A","FSC-H")))

2.4 Manually Gate Live Cells

template <- rbind(template, gate_draw(gs,
                                      parent = "Single Cells",
                                      alias = "Live Cells",
                                      channels = c("Alexa Fluor 405-A",
                                                   "Alexa Fluor 430-A")))

2.5 Automatically Gate T Cells

template <- rbind(template, app_pop(gs,
                                    alias = "T Cells",
                                    pop = "+",
                                    parent = "Live Cells",
                                    dims = "APC-Cy7-A,PE-A",
                                    gating_method = "flowClust",
                                    gating_args = "K=3,target=c(0,3)"))

2.6 Automatically Gate CD4 T Cells

template <- rbind(template, app_pop(gs,
                                    alias = "CD4 T Cells",
                                    pop = "+",
                                    parent = "T Cells",
                                    dims = "Alexa Fluor 700-A,Alexa Fluor 488-A",
                                    gating_method = "flowClust",
                                    gating_args = "K=3,target=c(3,0)"))

2.7 Automatically Gate CD8 T Cells

template <- rbind(template, app_pop(gs,
                                    alias = "CD8 T Cells",
                                    pop = "+",
                                    parent = "T Cells",
                                    dims = "Alexa Fluor 700-A,Alexa Fluor 488-A",
                                    gating_method = "flowClust",
                                    gating_args = "K=3,target=c(0,3)"))

2.8 Manually Gate CD69+ CD4 T Cells

template <- rbind(template, gate_draw(gs,
                                      parent = "CD4 T Cells",
                                      alias = "CD69+ CD4 T Cells",
                                      channels = c("Alexa Fluor 647-A",
                                                   "7-AAD-A"),
                                      type = "interval",
                                      axis = "y"))

2.9 Manually Gate CD69+ CD8 T Cells

template <- rbind(template, gate_draw(gs,
                                      parent = "CD8 T Cells",
                                      alias = "CD69+ CD8 T Cells",
                                      channels = c("Alexa Fluor 647-A",
                                                   "7-AAD-A"),
                                      type = "interval",
                                      axis = "y"))

2.10 Save gatingTemplate for Future Use

write.csv(template, "gatingTemplate.csv", row.names = FALSE)

2.11 Applying a Saved gatingTemplate

# Assign Activation flowSet to fs
fs <- Activation

# Add fs to a GatingSet
gs <- GatingSet(fs)

# Apply compensation
gs <- compensate(gs, fs[[1]]@description$SPILL)

# Transform fluorescent channels
trans <- estimateLogicle(gs[[4]], cyto_fluor_channels(gs))
gs <- transform(gs, trans)

# Apply gatingTemplate
gt <- gatingTemplate("gatingTemplate.csv")
gating(gt,gs)

# Visualise Gating Scheme
cyto_plot_gating_scheme(gs[[4]])

3. More Information

For more information on manual gating using CytoRSuite refer to Gating Functions and Gate Manipulation vignettes. For more information on automated gating using openCyto refer to this Gating Methods vignette.