Hi,

I am getting the following error when running the pipeline: "Error in [.data.frame(a, , "file") : undefined columns selected"

The data is FCS files after staining correction

Any idea why?

Thanks,

Niv

> head(read.csv("backbone_selection_file.csv"))
   name desc     type
1 FSC-A <NA>  discard
2 FSC-H <NA> backbone
3 FSC-W <NA> backbone
4 SSC-A <NA>  discard
5 SSC-H <NA> backbone
6 SSC-W <NA> backbone


> imputed_data <- infinity_flow("FCS","output",backbone_selection_file = "backbone_selection_file.csv")
Using /tmp/RtmpBa54s0 temporary directory to store intermediary results as no non-temporary directory has been specified
Using directories...
    input: FCS
    intermediary: /tmp/RtmpBa54s0
    subset: /tmp/RtmpBa54s0/subsetted_fcs
    rds: /tmp/RtmpBa54s0/rds
    annotation: /tmp/RtmpBa54s0/annotation.csv
    output: output
Parsing and subsampling input data
    Downsampling to Inf events per input file
    Concatenating expression matrices
    Writing to disk
Logicle-transforming the data
    Backbone data
    Exploratory data
    Writing to disk
    Transforming expression matrix
    Writing to disk
Harmonizing backbone data
    Scaling expression matrices
    Writing to disk
Fitting regression models
    Randomly selecting 50% of the subsetted input files to fit models
    Fitting...
        XGBoost

  |++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=17m 58s
    1078.243 seconds
Imputing missing measurements
    Randomly drawing events to predict from the test set
    Imputing...
        XGBoost

  |++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=09s  
    8.708082 seconds
    Concatenating predictions
    Writing to disk
Performing dimensionality reduction
05:39:53 UMAP embedding parameters a = 1.262 b = 1.003
05:39:53 Read 18000 rows and found 12 numeric columns
05:39:53 Using Annoy for neighbor search, n_neighbors = 15
05:39:53 Building Annoy index with metric = euclidean, n_trees = 50
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
05:39:55 Writing NN index file to temp file /tmp/RtmpBa54s0/file13ba5f6d30c0
05:39:55 Searching Annoy index using 1 thread, search_k = 1500
05:39:59 Annoy recall = 100%
05:40:00 Commencing smooth kNN distance calibration using 1 thread
05:40:02 Initializing from normalized Laplacian + noise
05:40:02 Commencing optimization for 1000 epochs, with 371826 positive edges using 1 thread
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
05:40:42 Optimization finished
Exporting results
Error in `[.data.frame`(a, , "file") : undefined columns selected

> sessionInfo( )
R version 4.0.5 (2021-03-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 18.04.5 LTS

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.7.1
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.7.1

Random number generation:
 RNG:     L'Ecuyer-CMRG 
 Normal:  Inversion 
 Sample:  Rejection 

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

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

other attached packages:
 [1] infinityFlow_1.0.0    flowCore_2.2.0        docstring_1.0.0       dplyr_1.0.7          
 [5] gplots_3.1.1          ggplot2_3.3.4         ComplexHeatmap_2.6.2  hdf5r_1.3.3          
 [9] SeuratDisk_0.0.0.9019 SeuratObject_4.0.2    Seurat_4.0.3         

loaded via a namespace (and not attached):
  [1] circlize_0.4.13       plyr_1.8.6            igraph_1.2.6          lazyeval_0.2.2       
  [5] sp_1.4-5              splines_4.0.5         listenv_0.8.0         scattermore_0.7      
  [9] digest_0.6.27         htmltools_0.5.1.1     fansi_0.5.0           magrittr_2.0.1       
 [13] tensor_1.5            cluster_2.1.2         ROCR_1.0-11           globals_0.14.0       
 [17] RcppParallel_5.1.4    matrixStats_0.59.0    spatstat.sparse_2.0-0 cytolib_2.2.1        
 [21] colorspace_2.0-1      ggrepel_0.9.1         xfun_0.24             crayon_1.4.1         
 [25] jsonlite_1.7.2        roxygen2_7.1.1        spatstat.data_2.1-0   survival_3.2-11      
 [29] zoo_1.8-9             glue_1.4.2            polyclip_1.10-0       gtable_0.3.0         
 [33] leiden_0.3.8          GetoptLong_1.0.5      future.apply_1.7.0    shape_1.4.6          
 [37] BiocGenerics_0.36.1   abind_1.4-5           scales_1.1.1          miniUI_0.1.1.1       
 [41] Rcpp_1.0.6            viridisLite_0.4.0     xtable_1.8-4          clue_0.3-59          
 [45] reticulate_1.20       spatstat.core_2.2-0   bit_4.0.4             matlab_1.0.2         
 [49] stats4_4.0.5          htmlwidgets_1.5.3     httr_1.4.2            RColorBrewer_1.1-2   
 [53] ellipsis_0.3.2        ica_1.0-2             pkgconfig_2.0.3       uwot_0.1.10          
 [57] deldir_0.2-10         utf8_1.2.1            tidyselect_1.1.1      rlang_0.4.11         
 [61] reshape2_1.4.4        later_1.2.0           munsell_0.5.0         tools_4.0.5          
 [65] xgboost_1.4.1.1       cli_3.0.1             generics_0.1.0        ggridges_0.5.3       
 [69] stringr_1.4.0         fastmap_1.1.0         goftest_1.2-2         knitr_1.33           
 [73] bit64_4.0.5           fitdistrplus_1.1-5    caTools_1.18.2        purrr_0.3.4          
 [77] RANN_2.6.1            pbapply_1.4-3         future_1.21.0         nlme_3.1-152         
 [81] mime_0.10             xml2_1.3.2            compiler_4.0.5        plotly_4.9.4.1       
 [85] png_0.1-7             spatstat.utils_2.2-0  tibble_3.1.2          stringi_1.6.2        
 [89] RSpectra_0.16-0       lattice_0.20-44       Matrix_1.3-4          vctrs_0.3.8          
 [93] pillar_1.6.1          lifecycle_1.0.0       spatstat.geom_2.2-0   lmtest_0.9-38        
 [97] GlobalOptions_0.1.2   RcppAnnoy_0.0.18      data.table_1.14.0     cowplot_1.1.1        
[101] bitops_1.0-7          irlba_2.3.3           raster_3.5-2          httpuv_1.6.1         
[105] patchwork_1.1.1       R6_2.5.0              promises_1.2.0.1      KernSmooth_2.23-20   
[109] gridExtra_2.3         RProtoBufLib_2.2.0    IRanges_2.24.1        parallelly_1.26.0    
[113] codetools_0.2-18      MASS_7.3-54           gtools_3.9.2          rjson_0.2.20         
[117] withr_2.4.2           sctransform_0.3.2     S4Vectors_0.28.1      mgcv_1.8-36          
[121] parallel_4.0.5        terra_1.4-11          rpart_4.1-15          tidyr_1.1.3          
[125] Cairo_1.5-12.2        Rtsne_0.15            Biobase_2.50.0        shiny_1.6.0