I am having problems with FCS3.2 format using some of the standard packages for fcs parsing. Packages were installed with Bioconductor on Feb 17 2024 and R 4.3.2. Was having problems even installing these packages, particularly CytoML, on earlier R versions.

Are there any other options for reading and parsing fcs and wsp files? I am trying to convert these file types to a table with all parameter and gating info for machine learning purposes.

> fc <- as_tibble(exprs(read.FCS(fcs,truncate_max_range = F)))
Warning message:
In readFCSheader(con) :
  The flowCore package does not fully support FCS3.2 yet
> fc <- fc %>% mutate(imageid = paste0("id", sprintf("%0.8d", 0:(dim(fc)[1]-1)))) #Add imageid
> gs  <- flowjo_to_gatingset(open_flowjo_xml(wsp, sample_names_from="sampleNode"), name = 1) #flowWorkspace package
Error: This does not seem to be a valid FCS2.0, FCS3.0 or FCS3.1 file

sessionInfo( )
R version 4.3.2 (2023-10-31)
Platform: x86_64-apple-darwin20 (64-bit)
Running under: macOS Ventura 13.5

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.3-x86_64/Resources/lib/libRblas.0.dylib 
LAPACK: /Library/Frameworks/R.framework/Versions/4.3-x86_64/Resources/lib/libRlapack.dylib;  LAPACK version 3.11.0

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

time zone: Europe/Berlin
tzcode source: internal

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

other attached packages:
 [1] lubridate_1.9.3      forcats_1.0.0        stringr_1.5.1       
 [4] dplyr_1.1.4          purrr_1.0.2          readr_2.1.5         
 [7] tidyr_1.3.1          tibble_3.2.1         ggplot2_3.4.4       
[10] tidyverse_2.0.0      flowWorkspace_4.14.2 CytoML_2.14.0       
[13] flowCore_2.14.1      optparse_1.7.4      

loaded via a namespace (and not attached):
 [1] utf8_1.2.4          generics_0.1.3      tcltk_4.3.2        
 [4] stringi_1.8.3       lattice_0.22-5      hms_1.1.3          
 [7] magrittr_2.0.3      timechange_0.3.0    grid_4.3.2         
[10] RColorBrewer_1.1-3  ggcyto_1.30.0       plyr_1.8.9         
[13] jsonlite_1.8.8      graph_1.80.0        gridExtra_2.3      
[16] BiocManager_1.30.22 fansi_1.0.6         scales_1.3.0       
[19] XML_3.99-0.16.1     Rgraphviz_2.46.0    getopt_1.20.4      
[22] cli_3.6.2           rlang_1.1.3         RProtoBufLib_2.14.0
[25] Biobase_2.62.0      munsell_0.5.0       withr_3.0.0        
[28] yaml_2.3.8          cytolib_2.14.1      tools_4.3.2        
[31] ncdfFlow_2.48.0     tzdb_0.4.0          colorspace_2.1-0   
[34] BiocGenerics_0.48.1 vctrs_0.6.5         R6_2.5.1           
[37] matrixStats_1.2.0   stats4_4.3.2        lifecycle_1.0.4    
[40] zlibbioc_1.48.0     S4Vectors_0.40.2    RBGL_1.78.0        
[43] pkgconfig_2.0.3     pillar_1.9.0        hexbin_1.28.3      
[46] gtable_0.3.4        data.table_1.15.0   glue_1.7.0         
[49] Rcpp_1.0.12         tidyselect_1.2.0    compiler_4.3.2