Error message when ploting .boundary gates

[schevrie]

I'm new to OpenCyto and try to use it to apply automatic gates to cytof data.

When I tried to apply a boundary gate using the following code:

g <- openCyto:::.boundary(ff_QC, channels = chnl, min = c(5, 0), max=c(7.5,2)) p <- autoplot(ff_QC, x = chnl[1], y = chnl[2], bins = 128) p + geom_gate(g)

I got this error message:

Error in sum(edges.lengths) : invalid 'type' (list) of argument

I reproduced the same error when using the dataset and code available here: https://www.bioconductor.org/packages/devel/bioc/vignettes/openCyto/inst/doc/HowToAutoGating.html

gs <- load_gs(system.file("extdata/gs_bcell_auto", package = "flowWorkspaceData"))

fr <- getData(gs[[1]], "root") chnl <- c("FSC-A", "SSC-A") g <- openCyto:::.boundary(fr, channels = chnl, min = c(0, 0), max=c(2.5e5,2.5e5)) p <- autoplot(fr, x = chnl[1], y = chnl[2]) p + geom_gate(g)

The 1D gating methods based on mindensity works well and the plot is correctly displayed as in the tutorial.

Here is my session info & thanks in advance for your help

sessionInfo() R version 3.5.0 (2018-04-23) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Ubuntu 16.04.4 LTS

Matrix products: default BLAS: /usr/lib/libblas/libblas.so.3.6.0 LAPACK: /usr/lib/lapack/liblapack.so.3.6.0

locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_US.UTF-8
[8] LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

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

other attached packages: [1] hexbin_1.27.2 ggcyto_1.8.2 openCyto_1.18.0 flowWorkspace_3.28.1 ncdfFlow_2.26.0 BH_1.66.0-1 RcppArmadillo_0.9.100.5.0 [8] flowViz_1.44.0 lattice_0.20-35 dplyr_0.7.6 bbRtools_0.5 ggplot2_3.0.0 flowCore_1.46.1 CATALYST_1.4.2

loaded via a namespace (and not attached): [1] shinydashboard_0.7.0 R.utils_2.6.0 ks_1.11.3 tidyselect_0.2.4 htmlwidgets_1.2 grid_3.5.0 BiocParallel_1.14.2
[8] Rtsne_0.13 munsell_0.5.0 destiny_2.10.2 codetools_0.2-15 DT_0.4 miniUI_0.1.1.1 withr_2.1.2
[15] colorspace_1.3-2 Biobase_2.40.0 rstudioapi_0.7 stats4_3.5.0 flowClust_3.18.0 robustbase_0.93-2 vcd_1.4-4
[22] cytofkit_1.12.0 VIM_4.7.0 TTR_0.23-3 labeling_0.3 GenomeInfoDbData_1.1.0 mnormt_1.5-5 MCMCpack_1.4-3
[29] coda_0.19-1 TH.data_1.0-9 ggthemes_4.0.0 doParallel_1.0.11 R6_2.2.2 GenomeInfoDb_1.16.0 clue_0.3-55
[36] pdist_1.2 RcppEigen_0.3.3.4.0 VGAM_1.0-5 bitops_1.0-6 DelayedArray_0.6.5 assertthat_0.2.0 promises_1.0.1
[43] scales_1.0.0 multcomp_1.4-8 nnet_7.3-12 gtable_0.2.0 mcmc_0.9-5 sandwich_2.4-0 rlang_0.2.2
[50] MatrixModels_0.4-1 scatterplot3d_0.3-41 GlobalOptions_0.1.0 splines_3.5.0 lazyeval_0.2.1 shinyBS_0.61 reshape2_1.4.3
[57] abind_1.4-5 httpuv_1.4.5 IDPmisc_1.1.17 RBGL_1.56.0 tools_3.5.0 tcltk_3.5.0 gplots_3.0.1
[64] RColorBrewer_1.1-2 proxy_0.4-22 BiocGenerics_0.26.0 Rcpp_0.12.18 plyr_1.8.4 zlibbioc_1.26.0 purrr_0.2.5
[71] RCurl_1.95-4.11 FlowSOM_1.12.0 GetoptLong_0.1.7 S4Vectors_0.18.3 zoo_1.8-3 SummarizedExperiment_1.10.1 haven_1.1.2
[78] ggrepel_0.8.0 cluster_2.0.7-1 fda_2.4.8 magrittr_1.5 data.table_1.11.4 openxlsx_4.1.0 SparseM_1.77
[85] circlize_0.4.4 colourpicker_1.0 lmtest_0.9-36 RANN_2.6 mvtnorm_1.0-8 matrixStats_0.54.0 hms_0.4.2
[92] shinyjs_1.0 mime_0.5 xtable_1.8-2 smoother_1.1 XML_3.98-1.15 rio_0.5.10 mclust_5.4.1
[99] readxl_1.1.0 IRanges_2.14.10 gridExtra_2.3 shape_1.4.4 compiler_3.5.0 tibble_1.4.2 flowStats_3.38.0
[106] KernSmooth_2.23-15 crayon_1.3.4 R.oo_1.22.0 htmltools_0.3.6 mgcv_1.8-24 corpcor_1.6.9 pcaPP_1.9-73
[113] later_0.7.3 tidyr_0.8.1 rrcov_1.4-4 ComplexHeatmap_1.18.1 MASS_7.3-50 boot_1.3-20 Matrix_1.2-14
[120] car_3.0-0 permute_0.9-4 gdata_2.18.0 R.methodsS3_1.7.1 parallel_3.5.0 bindr_0.1.1 igraph_1.2.2
[127] Rtsne.multicore_0.0.99 GenomicRanges_1.32.6 forcats_0.3.0 pkgconfig_2.0.2 foreign_0.8-71 laeken_0.4.6 sp_1.3-1
[134] plotly_4.8.0 foreach_1.4.4 XVector_0.20.0 drc_3.0-1 stringr_1.3.1 digest_0.6.15 tsne_0.1-3
[141] ConsensusClusterPlus_1.44.0 vegan_2.5-2 graph_1.58.0 cellranger_1.1.0 curl_3.2 shiny_1.1.0 gtools_3.8.1
[148] quantreg_5.36 rjson_0.2.20 nlme_3.1-137 jsonlite_1.5 bindrcpp_0.2.2 carData_3.0-1 viridisLite_0.3.0
[155] limma_3.36.2 pillar_1.3.0 shinyFiles_0.7.0 httr_1.3.1 plotrix_3.7-2 DEoptimR_1.0-8 survival_2.42-6
[162] glue_1.3.0 xts_0.11-0 zip_1.0.0 iterators_1.0.10 Rgraphviz_2.24.0 class_7.3-14 stringi_1.2.4
[169] nnls_1.4 caTools_1.17.1.1 latticeExtra_0.6-28 e1071_1.7-0

[mikejiang]

I can't reproduce your error with the same code below

library(openCyto)
library(ggcyto)
gs <- load_gs(system.file("extdata/gs_bcell_auto", package = "flowWorkspaceData"))
fr <- getData(gs[[1]], "root")
chnl <- c("FSC-A", "SSC-A")
g <- openCyto:::.boundary(fr, channels = chnl, min = c(0, 0), max=c(2.5e5,2.5e5))
p <- autoplot(fr, x = chnl[1], y = chnl[2])
p + geom_gate(g)

Bioc release also runs and builds the vignette ok (that contains the same code) http://bioconductor.org/packages/3.7/bioc/vignettes/openCyto/inst/doc/HowToAutoGating.html

Can you double check it?

[gfinak]

I don't see the error either on R 3.6.0 .

[schevrie]

Thanks for your feedback. We tried it in different environments and eventually it worked. Unfortunately we couldn't identify the reason why it didn't work in the beginning...