How to import Cytobank into a GatingSet
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
## cytobank Experiment: tcell
## gatingML File: /tmp/RtmpAwqrjt/file19613c4c81ff/experiments/3637/cytobank_gate_ml2_v41.xml
## panel samples
## 1 Panel 1 1cytobank_experiment is a wrapper around the
ACS file, which can be inspected by various accessors.
## [1] "CytoTrol_CytoTrol_1.fcs"## # A tibble: 1 × 2
## panel samples
## <chr> <int>
## 1 Panel 1 1## $`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## # A tibble: 1 × 2
## panel sample
## <chr> <chr>
## 1 Panel 1 CytoTrol_CytoTrol_1.fcs## [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"## $CytoTrol_CytoTrol_1.fcs
## [1] "FSC-A" "FSC-H" "FSC-W" "SSC-A" "CD4"
## [6] "CD38 APC" "CD8 APCH7" "CD3" "HLA-DR V500" "CCR7 PE"
## [11] "CD45RA PECy7" "Time"## name Conditions Individuals
## CytoTrol_CytoTrol_1.fcs CytoTrol_CytoTrol_1.fcs condition1 ptid1Then import cytobank_experiment into
GatingSet
By default, the first panel
(i.e. panel_id = 1) will be imported. Change
panel_id argument to select different panel (if there are
more than one , which can be inspected by ce_get_panels
)
Alternatively, the import can be done by gatingML and
fcs files that are downloaded separately form Cytobank
without ACS.
xmlfile <- ce$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
## name Population
## <char> <char>
## 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
## <char> <int> <int>
## 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