Error in prepData(fs, panel, md, features = panel$fcs_colname) : all(unlist(md_cols) %in% names(md)) is not TRUE

[CalmRealistic]

Hi I am having en error when I reach prepDAta and I did not find the solution by searching it. This is the error Error in prepData(fs, panel, md, features = panel$fcs_colname) : all(unlist(md_cols) %in% names(md)) is not TRUE

FCS files have the same names as the md, nothing bizzare there.

This is my code

library(CATALYST) library(cowplot) library(flowCore) library(diffcyt) library(scater) library(SingleCellExperiment) library(readxl)

panel<- read_excel("Catalyst/ panel.xlsx") md<-read_excel("Catalyst/sample.data.xlsx") View(md)

fs <- read.flowSet(files = fcs_files, truncate_max_range = FALSE, ignore.text.offset=TRUE)

construct SingleCellExperiment

sce <- prepData(fs, panel, md, features = panel$fcs_colname)

This is the session info

R version 4.2.1 (2022-06-23)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Monterey 12.6.7

Matrix products: default
LAPACK: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib

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

attached base packages:
[1] stats4    stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] readxl_1.4.3                scater_1.24.0               ggplot2_3.4.2              
 [4] scuttle_1.6.3               diffcyt_1.16.0              flowCore_2.8.0             
 [7] cowplot_1.1.1               CATALYST_1.20.1             SingleCellExperiment_1.18.1
[10] SummarizedExperiment_1.26.1 Biobase_2.56.0              GenomicRanges_1.48.0       
[13] GenomeInfoDb_1.32.4         IRanges_2.30.1              S4Vectors_0.34.0           
[16] BiocGenerics_0.42.0         MatrixGenerics_1.8.1        matrixStats_1.0.0          

loaded via a namespace (and not attached):
  [1] backports_1.4.1             circlize_0.4.15             drc_3.0-1                  
  [4] plyr_1.8.8                  igraph_1.5.0.1              ConsensusClusterPlus_1.60.0
  [7] splines_4.2.1               BiocParallel_1.30.4         scattermore_1.2            
 [10] TH.data_1.1-2               digest_0.6.33               foreach_1.5.2              
 [13] htmltools_0.5.5             viridis_0.6.4               fansi_1.0.4                
 [16] magrittr_2.0.3              ScaledMatrix_1.4.1          CytoML_2.8.1               
 [19] cluster_2.1.4               doParallel_1.0.17           limma_3.52.4               
 [22] aws.signature_0.6.0         ComplexHeatmap_2.12.1       RcppParallel_5.1.7         
 [25] sandwich_3.0-2              flowWorkspace_4.8.0         cytolib_2.8.0              
 [28] jpeg_0.1-10                 colorspace_2.1-0            ggrepel_0.9.3              
 [31] xfun_0.40                   dplyr_1.1.2                 crayon_1.5.2               
 [34] RCurl_1.98-1.12             jsonlite_1.8.7              hexbin_1.28.3              
 [37] graph_1.74.0                lme4_1.1-34                 survival_3.5-5             
 [40] zoo_1.8-12                  iterators_1.0.14            glue_1.6.2                 
 [43] polyclip_1.10-4             gtable_0.3.3                nnls_1.4                   
 [46] zlibbioc_1.42.0             XVector_0.36.0              GetoptLong_1.0.5           
 [49] DelayedArray_0.22.0         ggcyto_1.24.1               BiocSingular_1.12.0        
 [52] car_3.1-2                   Rgraphviz_2.40.0            shape_1.4.6                
 [55] abind_1.4-5                 scales_1.2.1                pheatmap_1.0.12            
 [58] mvtnorm_1.2-2               edgeR_3.38.4                DBI_1.1.3                  
 [61] rstatix_0.7.2               Rcpp_1.0.11                 plotrix_3.8-2              
 [64] viridisLite_0.4.2           clue_0.3-64                 rsvd_1.0.5                 
 [67] FlowSOM_2.4.0               httr_1.4.6                  RColorBrewer_1.1-3         
 [70] pkgconfig_2.0.3             XML_3.99-0.14               farver_2.1.1               
 [73] deldir_1.0-9                locfit_1.5-9.8              utf8_1.2.3                 
 [76] tidyselect_1.2.0            rlang_1.1.1                 reshape2_1.4.4             
 [79] cellranger_1.1.0            munsell_0.5.0               tools_4.2.1                
 [82] cli_3.6.1                   generics_0.1.3              broom_1.0.5                
 [85] ggridges_0.5.4              aws.s3_0.3.21               evaluate_0.21              
 [88] stringr_1.5.0               fastmap_1.1.1               yaml_2.3.7                 
 [91] knitr_1.43                  purrr_1.0.2                 nlme_3.1-162               
 [94] sparseMatrixStats_1.8.0     RBGL_1.72.0                 xml2_1.3.5                 
 [97] compiler_4.2.1              rstudioapi_0.15.0           beeswarm_0.4.0             
[100] curl_5.0.1                  png_0.1-8                   ggsignif_0.6.4             
[103] tibble_3.2.1                tweenr_2.0.2                stringi_1.7.12             
[106] lattice_0.21-8              Matrix_1.5-3                nloptr_2.0.3               
[109] vctrs_0.6.3                 pillar_1.9.0                lifecycle_1.0.3            
[112] GlobalOptions_0.1.2         BiocNeighbors_1.14.0        irlba_2.3.5.1              
[115] data.table_1.14.8           bitops_1.0-7                colorRamps_2.3.1           
[118] R6_2.5.1                    latticeExtra_0.6-30         gridExtra_2.3              
[121] RProtoBufLib_2.8.0          vipor_0.4.5                 codetools_0.2-19           
[124] boot_1.3-28.1               MASS_7.3-60                 gtools_3.9.4               
[127] rjson_0.2.21                withr_2.5.0                 multcomp_1.4-25            
[130] GenomeInfoDbData_1.2.8      parallel_4.2.1              ncdfFlow_2.42.1            
[133] beachmat_2.12.0             grid_4.2.1                  minqa_1.2.5                
[136] tidyr_1.3.0                 ggpointdensity_0.1.0        DelayedMatrixStats_1.18.2  
[139] rmarkdown_2.23              carData_3.0-5               Rtsne_0.16                 
[142] ggpubr_0.6.0                ggnewscale_0.4.9            ggforce_0.4.1              
[145] base64enc_0.1-3             ggbeeswarm_0.7.2            interp_1.1-4   

Thank you 

[CalmRealistic]

I tried this, but it did not work

  md_cols = list(file = "Filename",  factors = c("Response",
    "Batch"))
    ids0 <- md[[md_cols$file]]
    ids1 <- fsApply(fs, identifier)
    ids2 <- keyword(fs, "FILENAME")
    if (length(unlist(ids2)) == length(fs))
        ids2 <- basename(ids2)
    check1 <- all(ids1 %in% ids0)
    check2 <- all(ids2 %in% ids0)
    ids_use <- which(c(check1, check2))[1]
    ids <- list(ids1, ids2)[[ids_use]]
    if (is.null(ids)) {
        stop("Couldn't match 'flowSet'/FCS filenames\n", 
            "with those listed in 'md[[md_cols$file]]'.")
    } else {
        # reorder 'flowSet' frames according to metadata table
        fs <- fs[match(md[[md_cols$file]], ids)]
    }

[HelenaLC]

The error says “all(unlist(md_cols) %in% names(md)) is not TRUE”, so could you please post names(md) and how your running prepData() when the error occurs? That check that fails is independent of the FCS files.

[CalmRealistic]

This is what names(md) gives [1] "Filename" "Group" "Number" "Response" "Batch"

and I am sorry, I did not understand the "how I am running prepdata".

[HelenaLC]

Yeah so the names(md) dont match any of the defaults of the md_cols argument in prepData(). Have a look at ?prepData and adapt the md_cols argument to match your md table, and the error should be resolved. Or, alternatively, rename your md columns to match the defaults.

[CalmRealistic]

I changed my excell and now I have this I renamed some

names(md) [1] "file_name" "Group" "sample_id" "Condition" "Batch"

And would like some additional factors, but my code is wrong

factors <- list(factors = c("condition", "Group", "Batch")) sce <- prepData(fs, panel, md, features = panel$fcs_colname, md_cols=factors)

what should it be? 

[HelenaLC]

…Capital letter “Condition”?

[CalmRealistic]

Thank you, I guess the capital letter worked, because R was running really long time, but I will do the rest on my work computer, since the one I have crushed 2 times already.