GatingSet2cytobank of gs from flowWorkspace fails

[floklemm]

Hi,

I am trying to use the FlowWorkspace package to extract my manual gating set from a FlowJo v10.1 workspace and export that as a GatingML file using "GatingSet2Cytobank". However this fails repeatedly. Here is my code and the console output:

library(CytoML)
library(flowWorkspace)
setwd("/Users/fklemm/Documents/FCM_analysis")
wsp <- "/Users/fklemm/Documents/FCM_analysis/input/csv_flowjo/GBM_46/gbm_46.wsp"
ws <- openWorkspace(wsp)
gs <- parseWorkspace(ws, name=1)
Parsing 1 samples
windows version of flowJo workspace recognized.
version X
Creating ncdfFlowSet...
All FCS files have the same following channels:
FSC-A
FSC-H
FSC-W
SSC-A
SSC-H
SSC-W
FITC-A
BV421-A
Alexa Fluor 700-A
PE-A
BV786-A
APC-A
BV711-A
BV605-A
PerCP-Cy5-5-A
PE-Cy7-A
BV650-A
405nm-585/42-A
PE-Texas Red-A
PE-Cy5-5-A
APC-Cy7-A
Time
done!
loading data: /Users/fklemm/Documents/FCM_analysis/input/csv_flowjo/GBM_46/LAU_GBM_46_bulk_full_panel_002.fcs
Compensating
gating ...
write LAU_GBM_46_bulk_full_panel_002.fcs_2175523 to empty cdf slot...
done!
plot(gs[[1]])
gh <- gs[[1]]
GatingSet2cytobank(gs, "./input/csv_flowjo/GBM_46/gbm_46_gs.xml")
Error in get(y, obj@indices) :
object 'LAU_GBM_46_bulk_full_panel_002.fcs' not found
In addition: Warning message:
In GatingSet2cytobank(gs, "./input/csv_flowjo/GBM_46/gbm_46_gs.xml") :
With 'cytobank.default.scale' set to 'TRUE', data and gates will be re-transformed with cytobank's default scaling settings, which may affect how gates look like.`

Here is my session info:
`> sessionInfo()
R version 3.3.1 (2016-06-21)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: OS X 10.11.6 (El Capitan)

locale:
[1] C

attached base packages:
[1] stats graphics grDevices utils datasets methods base

other attached packages:
[1] flowWorkspace_3.20.2 ncdfFlow_2.20.0 BH_1.62.0-1
[4] RcppArmadillo_0.7.600.1.0 CytoML_1.0.0 ggplot2_2.2.0
[7] Rtsne_0.11 FlowSOM_1.6.0 igraph_1.0.1
[10] flowCore_1.40.3

loaded via a namespace (and not attached):
[1] Biobase_2.34.0 splines_3.3.1 jsonlite_1.1
[4] ConsensusClusterPlus_1.38.0 R.utils_2.5.0 gtools_3.5.0
[7] shiny_0.14.2 assertthat_0.1 stats4_3.3.1
[10] latticeExtra_0.6-28 RBGL_1.50.0 robustbase_0.92-7
[13] lattice_0.20-34 quantreg_5.29 RUnit_0.4.31
[16] digest_0.6.10 RColorBrewer_1.1-2 colorspace_1.3-2
[19] htmltools_0.3.5 httpuv_1.3.3 Matrix_1.2-7.1
[22] R.oo_1.21.0 plyr_1.8.4 multicool_0.1-10
[25] pcaPP_1.9-61 XML_3.98-1.5 misc3d_0.8-4
[28] tsne_0.1-3 SparseM_1.74 fda_2.4.4
[31] zlibbioc_1.20.0 xtable_1.8-2 corpcor_1.6.8
[34] mvtnorm_1.0-5 scales_0.4.1 MatrixModels_0.4-1
[37] openCyto_1.12.1 flowStats_3.32.0 tibble_1.2
[40] flowViz_1.38.0 BiocGenerics_0.20.0 hexbin_1.27.1
[43] lazyeval_0.2.0 mnormt_1.5-5 magrittr_1.5
[46] IDPmisc_1.1.17 mime_0.5 mcmc_0.9-4
[49] ks_1.10.4 R.methodsS3_1.7.1 MASS_7.3-45
[52] graph_1.52.0 tools_3.3.1 data.table_1.10.0
[55] flowClust_3.12.1 matrixStats_0.51.0 stringr_1.1.0
[58] MCMCpack_1.3-8 munsell_0.4.3 cluster_2.0.5
[61] flowUtils_1.38.0 grid_3.3.1 htmlwidgets_0.8
[64] base64enc_0.1-3 codetools_0.2-15 gtable_0.2.0
[67] DBI_0.5-1 rrcov_1.4-3 R6_2.2.0
[70] gridExtra_2.2.1 knitr_1.15.1 dplyr_0.5.0
[73] clue_0.3-52 KernSmooth_2.23-15 Rgraphviz_2.18.0
[76] stringi_1.1.2 parallel_3.3.1 Rcpp_0.12.8
[79] rgl_0.96.0 DEoptimR_1.0-8 coda_0.19-1

`

I ultimately want to use the GatingML file within FlowSOM because the xml provided by FlowJo uses cryptic IDs for the gates that makes picking populations tricky.

Thanks a lot, Florian.