This vignette demonstrates how the gatingML files exported from Cytobank can be imported into R as a GatingSet object.
library(flowWorkspace)
library(CytoML)
acs <- system.file("extdata/cytobank_experiment.acs", package = "CytoML")
Create cytobank_experiment
object from the ACS bundle exported from Cytobank
ce <- open_cytobank_experiment(acs)
ce
## cytobank Experiment: tcell
## gatingML File: /tmp/Rtmpyb3OY4/file2f57781978f666/experiments/3637/cytobank_gate_ml2_v41.xml
## panel samples
## 1 Panel 1 1
cytobank_experiment is a wrapper around the ACS
file, which can be inspected by various accessors.
sampleNames(ce)
## [1] "CytoTrol_CytoTrol_1.fcs"
ce_get_panels(ce)
## # A tibble: 1 x 2
## panel samples
## <chr> <int>
## 1 Panel 1 1
ce_get_compensations(ce)
## $`CytoTrol_CytoTrol_1.fcs - spill string`
## B710-A R660-A R780-A V450-A V545-A G560-A
## B710-A 1.00000e+00 3.14389e-02 0.190966000 0.003057570 0.00204723 3.44241e-04
## R660-A 5.53798e-03 1.00000e+00 0.176812000 0.000000000 0.00000000 0.00000e+00
## R780-A 9.95863e-05 9.84766e-03 1.000000000 0.000000000 0.00000000 0.00000e+00
## V450-A 0.00000e+00 8.90985e-05 0.000000000 1.000000000 0.45119500 1.08275e-04
## V545-A 2.47709e-03 5.23516e-04 0.000000000 0.037961500 1.00000000 6.36181e-05
## G560-A 1.17224e-01 1.64272e-03 0.000332153 0.000000000 0.00000000 1.00000e+00
## G780-A 1.42052e-02 4.56896e-04 0.175402000 0.000089025 0.00000000 4.09687e-02
## G780-A
## B710-A 0.07193380
## R660-A 0.00661890
## R780-A 0.03539970
## V450-A 0.00000000
## V545-A 0.00000000
## G560-A 0.00921936
## G780-A 1.00000000
##
## $`CytoTrol_CytoTrol_1.fcs - spill string`
## B710-A R660-A R780-A V450-A V545-A G560-A
## B710-A 1.00000e+00 3.14389e-02 0.190966000 0.003057570 0.00204723 3.44241e-04
## R660-A 5.53798e-03 1.00000e+00 0.176812000 0.000000000 0.00000000 0.00000e+00
## R780-A 9.95863e-05 9.84766e-03 1.000000000 0.000000000 0.00000000 0.00000e+00
## V450-A 0.00000e+00 8.90985e-05 0.000000000 1.000000000 0.45119500 1.08275e-04
## V545-A 2.47709e-03 5.23516e-04 0.000000000 0.037961500 1.00000000 6.36181e-05
## G560-A 1.17224e-01 1.64272e-03 0.000332153 0.000000000 0.00000000 1.00000e+00
## G780-A 1.42052e-02 4.56896e-04 0.175402000 0.000089025 0.00000000 4.09687e-02
## G780-A
## B710-A 0.07193380
## R660-A 0.00661890
## R780-A 0.03539970
## V450-A 0.00000000
## V545-A 0.00000000
## G560-A 0.00921936
## G780-A 1.00000000
##
## $`CytoTrol_CytoTrol_1.fcs - spill string`
## B710-A R660-A R780-A V450-A V545-A G560-A
## B710-A 1.00000e+00 3.14389e-02 0.190966000 0.003057570 0.00204723 3.44241e-04
## R660-A 5.53798e-03 1.00000e+00 0.176812000 0.000000000 0.00000000 0.00000e+00
## R780-A 9.95863e-05 9.84766e-03 1.000000000 0.000000000 0.00000000 0.00000e+00
## V450-A 0.00000e+00 8.90985e-05 0.000000000 1.000000000 0.45119500 1.08275e-04
## V545-A 2.47709e-03 5.23516e-04 0.000000000 0.037961500 1.00000000 6.36181e-05
## G560-A 1.17224e-01 1.64272e-03 0.000332153 0.000000000 0.00000000 1.00000e+00
## G780-A 1.42052e-02 4.56896e-04 0.175402000 0.000089025 0.00000000 4.09687e-02
## G780-A
## B710-A 0.07193380
## R660-A 0.00661890
## R780-A 0.03539970
## V450-A 0.00000000
## V545-A 0.00000000
## G560-A 0.00921936
## G780-A 1.00000000
ce_get_samples(ce)
## # A tibble: 1 x 2
## panel sample
## <chr> <chr>
## 1 Panel 1 CytoTrol_CytoTrol_1.fcs
ce_get_channels(ce)
## [1] "FSC-A" "FSC-H" "FSC-W" "SSC-A" "B710-A" "R660-A" "R780-A" "V450-A"
## [9] "V545-A" "G560-A" "G780-A" "Time"
ce_get_markers(ce)
## $CytoTrol_CytoTrol_1.fcs
## [1] "FSC-A" "FSC-H" "FSC-W" "SSC-A" "CD4"
## [6] "CD38 APC" "CD8 APCH7" "CD3" "HLA-DR V500" "CCR7 PE"
## [11] "CD45RA PECy7" "Time"
pData(ce)
## name Conditions Individuals
## CytoTrol_CytoTrol_1.fcs CytoTrol_CytoTrol_1.fcs condition1 ptid1
Then import cytobank_experiment
into GatingSet
gs <- cytobank_to_gatingset(ce)
By default, the first panel
(i.e. panel_id = 1
) will be imported. Change panel_id
argument to select different panel (if there are more than one , which can be inspected by ce_get_panels
)
Alternatively, the import can be done by gatingML
and fcs
files that are downloaded separately form Cytobank without ACS
.
xmlfile <- ce$gatingML
fcsFiles <- list.files(ce$fcsdir, full.names = TRUE)
gs <- cytobank_to_gatingset(xmlfile, fcsFiles)
However, it doesn’t have the information from yaml
file (part of ACS
). E.g. sample tags (i.e. pData
) and customized markernames. So it is recommended to import ACS
.
Inspect the results
library(ggcyto)
## Plot the gates
autoplot(gs[[1]])
# Extract the population statistics
gs_pop_get_count_fast(gs, statType = "count")
## name Population
## 1: CytoTrol_CytoTrol_1.fcs /not debris
## 2: CytoTrol_CytoTrol_1.fcs /not debris/singlets
## 3: CytoTrol_CytoTrol_1.fcs /not debris/singlets/CD3
## 4: CytoTrol_CytoTrol_1.fcs /not debris/singlets/CD3/CD8
## 5: CytoTrol_CytoTrol_1.fcs /not debris/singlets/CD3/CD8/CD8_Q2
## 6: CytoTrol_CytoTrol_1.fcs /not debris/singlets/CD3/CD4
## 7: CytoTrol_CytoTrol_1.fcs /not debris/singlets/CD3/CD4/Q1
## 8: CytoTrol_CytoTrol_1.fcs /not debris/singlets/CD3/CD4/Q2
## 9: CytoTrol_CytoTrol_1.fcs /not debris/singlets/CD3/CD4/Q4
## 10: CytoTrol_CytoTrol_1.fcs /not debris/singlets/CD3/CD4/Q3
## 11: CytoTrol_CytoTrol_1.fcs /not debris/singlets/CD3/CD8/CD8_Q2/CD38 range
## 12: CytoTrol_CytoTrol_1.fcs /not debris/singlets/CD3/CD8/CD8_Q2/HLA range
## Parent Count ParentCount
## 1: root 87876 119531
## 2: /not debris 79845 87876
## 3: /not debris/singlets 53135 79845
## 4: /not debris/singlets/CD3 12862 53135
## 5: /not debris/singlets/CD3/CD8 2331 12862
## 6: /not debris/singlets/CD3 33653 53135
## 7: /not debris/singlets/CD3/CD4 419 33653
## 8: /not debris/singlets/CD3/CD4 11429 33653
## 9: /not debris/singlets/CD3/CD4 4119 33653
## 10: /not debris/singlets/CD3/CD4 17686 33653
## 11: /not debris/singlets/CD3/CD8/CD8_Q2 2331 2331
## 12: /not debris/singlets/CD3/CD8/CD8_Q2 2315 2331