R Session Aborts when calling flowjo_to_gatingset() more than once about cytoml HOT 3 OPEN

I was running into the same issue. I had CytoML under version 2.8.1 I believe. After updating it to 2.10.0, the issue is now resolved for me.

from cytoml.

Hi,
I have the same issue. I am running R version 4.2.1 (2022-06-23 ucrt) -- "Funny-Looking Kid"
Copyright (C) 2022 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (64-bit)

flowjo_to_gatingset() works fine with the first group in the workspace, eg '97420-1-02 BAL Cells' in the following ouptput:

Groups in Workspace
Name Num.Samples
1 All Samples 38
2 97420-1-02 BAL Cells 6
3 97420-1-02 PBMCs 6
4 Compensation 14

But R completely aborts when trying to run: flowjo_to_gatingset(WS,name="97420-1-02 PBMCs",
keywords = c( "$FIL", "TBNM", "$DATE"), additional.sampleID = TRUE)

I also tried this code on a linux cluster running 'R/4.2.1-foss-2022a' and 'R-bundle-Bioconductor/3.15-foss-2022a-R-4.2.1' and after running the first flowjo_to_gatingset instance, it returns:

PBMC.gs <- flowjo_to_gatingset(WS, name="97415-1-04 PBMCs", keywords=c("$FIL", "TBNM", "$DATE"),additional.sampleID=TRUE)

*** caught segfault ***
address 0xfffffffffffffff7, cause 'memory not mapped'

Traceback:
1: (function (ws, group_id, subset, execute, path, cytoset, backend_dir, backend, includeGates, additional_keys, additional_sampleID, keywords, is_pheno_data_from_FCS, keyword_ignore_case, extend_val, extend_to, channel_ignore_case, leaf_bool, include_empty_tree, skip_faulty_gate, comps, transform, fcs_file_extension, greedy_match, fcs_parse_arg, num_threads = 1L) { .Call(_CytoML_parse_workspace, ws, group_id, subset, execute, path, cytoset, backend_dir, backend, includeGates, additional_keys, additional_sampleID, keywords, is_pheno_data_from_FCS, keyword_ignore_case, extend_val, extend_to, channel_ignore_case, leaf_bool, include_empty_tree, skip_faulty_gate, comps, transform, fcs_file_extension, greedy_match, fcs_parse_arg, num_threads)})(ws = <pointer: 0x10da1550>, group_id = 2, subset = list(), execute = TRUE, path = "", cytoset = <pointer: 0xdc92a70>, backend_dir = "/tmp/job.66346.hpc/Rtmp9cKpPF", backend = "h5", includeGates = TRUE, additional_keys = "$TOT", additional_sampleID = TRUE, keywords = c("$FIL", "TBNM", "$DATE"), is_pheno_data_from_FCS = FALSE, keyword_ignore_case = FALSE, extend_val = 0, extend_to = -4000, channel_ignore_case = FALSE, leaf_bool = TRUE, include_empty_tree = FALSE, skip_faulty_gate = FALSE, comps = list(), transform = TRUE, fcs_file_extension = ".fcs", greedy_match = FALSE, fcs_parse_arg = list(), num_threads = 1)
2: do.call(parse_workspace, args)
3: flowjo_to_gatingset(WS, name = "97415-1-04 PBMCs", keywords = c("$FIL", "TBNM", "$DATE"), additional.sampleID = TRUE)

Thanks for any help with this!
Bonnie

from cytoml.

Hi,
I appear to be seeing the same issue when running flowjo_to_gatingset() consecutively

gs <- flowjo_to_gatingset(ws, name = 3, path = dataDirFCS)

gs2 <- flowjo_to_gatingset(ws, name = 4, path = dataDirFCS)

Running the first call works perfectly, but the second throws the following error:

*** caught segfault ***
address 0xfffffffffffffff7, cause 'memory not mapped'
Traceback:
1: (function (ws, group_id, subset, execute, path, cytoset, backend_dir, backend, includeGates, additional_keys, additional_sampleID, keywords, is_pheno_data_from_FCS, keyword_ignore_case, extend_val, extend_to, channel_ignore_case, leaf_bool, include_empty_tree, skip_faulty_gate, comps, transform, fcs_file_extension, greedy_match, fcs_parse_arg, num_threads = 1L) { .Call(_CytoML_parse_workspace, ws, group_id, subset, execute, path, cytoset, backend_dir, backend, includeGates, additional_keys, additional_sampleID, keywords, is_pheno_data_from_FCS, keyword_ignore_case, extend_val, extend_to, channel_ignore_case, leaf_bool, include_empty_tree, skip_faulty_gate, comps, transform, fcs_file_extension, greedy_match, fcs_parse_arg, num_threads)})(ws = <pointer: 0x55a065164380>, group_id = 3, subset = list(), execute = TRUE, path = "/media/huw/DATA/220826_Microspheres_32-colours-V04/Unmixed", cytoset = <pointer: 0x55a05df03be0>, backend_dir = "/tmp/RtmpYq7oXF", backend = "h5", includeGates = TRUE, additional_keys = "$TOT", additional_sampleID = FALSE, keywords = character(0), is_pheno_data_from_FCS = FALSE, keyword_ignore_case = FALSE, extend_val = 0, extend_to = -4000, channel_ignore_case = FALSE, leaf_bool = TRUE, include_empty_tree = FALSE, skip_faulty_gate = FALSE, comps = list(), transform = TRUE, fcs_file_extension = ".fcs", greedy_match = FALSE, fcs_parse_arg = list(), num_threads = 1)
2: do.call(parse_workspace, args)
3: flowjo_to_gatingset(ws, name = 4, path = dataDirFCS)

Here is the output of sessionInfo()

R version 4.1.2 (2021-11-01)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 22.04.1 LTS

Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/atlas/libblas.so.3.10.3
LAPACK: /usr/lib/x86_64-linux-gnu/atlas/liblapack.so.3.10.3

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

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

other attached packages:
[1] CytoML_2.6.0

loaded via a namespace (and not attached):
[1] tidyselect_1.2.0 lattice_0.20-45 colorspace_2.0-3 vctrs_0.5.1 generics_0.1.3 stats4_4.1.2 yaml_2.3.6
[8] ncdfFlow_2.40.0 base64enc_0.1-3 RBGL_1.70.0 utf8_1.2.2 flowCore_2.6.0 XML_3.99-0.12 rlang_1.0.6
[15] hexbin_1.28.2 pillar_1.8.1 withr_2.5.0 glue_1.6.2 DBI_1.1.3 aws.s3_0.3.21 Rgraphviz_2.38.0
[22] BiocGenerics_0.40.0 RColorBrewer_1.1-3 plyr_1.8.8 matrixStats_0.63.0 jpeg_0.1-9 lifecycle_1.0.3 zlibbioc_1.40.0
[29] RProtoBufLib_2.6.0 munsell_0.5.0 gtable_0.3.1 cytolib_2.6.2 latticeExtra_0.6-30 Biobase_2.54.0 curl_4.3.3
[36] flowWorkspace_4.6.0 fansi_1.0.3 Rcpp_1.0.9 scales_1.2.1 S4Vectors_0.32.4 jsonlite_1.8.3 RcppParallel_5.1.5
[43] graph_1.72.0 deldir_1.0-6 interp_1.1-3 gridExtra_2.3 ggplot2_3.4.0 png_0.1-7 digest_0.6.30
[50] dplyr_1.0.10 grid_4.1.2 cli_3.4.1 tools_4.1.2 magrittr_2.0.3 tibble_3.1.8 aws.signature_0.6.0
[57] pkgconfig_2.0.3 data.table_1.14.6 xml2_1.3.3 assertthat_0.2.1 httr_1.4.4 rstudioapi_0.14 R6_2.5.1
[64] ggcyto_1.22.0 compiler_4.1.2

Your help getting to the bottom of this would be much appreacated!

H

from cytoml.