8000 do_GroupWiseDEPlot returns "Error in if (dmax - dmin < eps) { : missing value where TRUE/FALSE needed" · Issue #82 · enblacar/SCpubr · GitHub
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samgest opened this issue Feb 10, 2025 · 2 comments
Open

do_GroupWiseDEPlot returns "Error in if (dmax - dmin < eps) { : missing value where TRUE/FALSE needed" #82

samgest opened this issue Feb 10, 2025 · 2 comments

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@samgest
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samgest commented Feb 10, 2025

Hi, I'm trying to run plot the GroupWise_DE genes but I keep getting an error.

Given a Seurat v5 object "Malignant.Merged" with an SCTAssay as default:

> Malignant.Merged
An object of class Seurat 
45750 features across 74858 samples within 4 assays 
Active assay: SCT (19995 features, 3000 variable features)
 3 layers present: counts, data, scale.data
 3 other assays present: RNA, pathwaysmlm, tfsulm
 10 dimensional reductions calculated: pca, umap_unintegrated_SCT, harmony_SCT, umap_integrated_harmony_SCT, umap_unintegrated_harmony_SCT, pca_SCT_Feats, harmony_SCT_Feats, umap_integrated_harmony_SCT_Feats, umap_integrated_harmony_SCT_default, umap_integrated_harmony_SCT_umapLearn

Image

I run:

de_genes <- FindAllMarkers(Malignant.Merged, assay = "SCT", group.by = "malignantClustersOnly")

SCpubr::do_GroupwiseDEPlot(sample = Malignant.Merged,
                           de_genes = de_genes,
                           min.cutoff = 1
                           )

When trying to get the plot, the console returns this error:

Error in if (dmax - dmin < eps) { : missing value where TRUE/FALSE needed
In addition: Warning message:
In min(., na.rm = TRUE) : no non-missing arguments to min; returning Inf

The "de_markers" object looks like this:

head(de_markers)
        p_val avg_log2FC pct.1 pct.2 p_val_adj         cluster    gene
SERTAD1     0   1.074416 0.706 0.441         0 Sc. 2 - SERTAD1 SERTAD1
ATF3        0   1.745181 0.878 0.616         0 Sc. 2 - SERTAD1    ATF3
MAFF        0   1.115368 0.552 0.315         0 Sc. 2 - SERTAD1    MAFF
ANKRD37     0   1.357709 0.573 0.359         0 Sc. 2 - SERTAD1 ANKRD37
BTG2        0   1.256733 0.677 0.464         0 Sc. 2 - SERTAD1    BTG2
DNAJB4      0   1.537753 0.489 0.277         0 Sc. 2 - SERTAD1  DNAJB4


summary(de_markers)
 p_val               avg_log2FC        pct.1          pct.2              p_val_adj        cluster     
 Min.   :0.000e+00   Min.   : 0.1000   Min.   :0.0060   Min.   :0.0000   Min.   :0.0000   Sc. 2 - SERTAD1:10237  
 1st Qu.:0.000e+00   1st Qu.: 0.3191   1st Qu.:0.0490   1st Qu.:0.0280   1st Qu.:0.0000   Sc. 6 - CCL2   : 6721  
 Median :0.000e+00   Median : 0.5059   Median :0.1080   Median :0.0720   Median :0.0000   Sc. 11 - SLPI  : 6605  
 Mean   :3.949e-04   Mean   : 0.7463   Mean   :0.1768   Mean   :0.1321   Mean   :0.2106   Sc. 12 - TGFBI : 6590  
 3rd Qu.:3.726e-06   3rd Qu.: 0.8404   3rd Qu.:0.2230   3rd Qu.:0.1570   3rd Qu.:0.0745   Sc. 8 - SST    : 6178  
 Max.   :9.999e-03   Max.   :13.3652   Max.   :1.0000   Max.   :0.9990   Max.   :1.0000   Sc. 1 - N4BP2L2: 4948  
                                                                                          (Other)        :13443  
 gene          
 Length:54722      
 Class :character  
 Mode  :character

Thanks in advance!

> sessionInfo()
R version 4.4.2 (2024-10-31 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 26100)

Matrix products: default


locale:
[1] LC_COLLATE=English_Europe.utf8  LC_CTYPE=English_Europe.utf8    LC_MONETARY=English_Europe.utf8 LC_NUMERIC=C                   
[5] LC_TIME=English_Europe.utf8    

time zone: Europe/Madrid
tzcode source: internal

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

other attached packages:
 [1] convenience_1.0.0           rwty_1.0.2                  coda_0.19-4.1               ape_5.8-1                  
 [5] scran_1.34.0                psych_2.4.12                writexl_1.5.1               readxl_1.4.3               
 [9] Nebulosa_1.16.0             scCustomize_3.0.1           future_1.34.0               presto_1.0.0               
[13] glmGamPoi_1.18.0            clustree_0.5.1              ggraph_2.2.1                data.table_1.16.4          
[17] reshape2_1.4.4              DESeq2_1.46.0               GSVA_2.0.5                  BaseSet_0.9.0              
[21] reticulate_1.40.0           GSEABase_1.68.0             graph_1.84.1                annotate_1.84.0            
[25] XML_3.99-0.18               AnnotationDbi_1.68.0        splitstackshape_1.4.8       lubridate_1.9.4            
[29] forcats_1.0.0               stringr_1.5.1               purrr_1.0.2                 readr_2.1.5                
[33] tidyr_1.3.1                 tidyverse_2.0.0             tibble_3.2.1                dplyr_1.1.4                
[37] patchwork_1.3.0             ComplexHeatmap_2.22.0       scater_1.34.0               ggplot2_3.5.1              
[41] scuttle_1.16.0              SingleCellExperiment_1.28.1 SummarizedExperiment_1.36.0 Biobase_2.66.0             
[45] GenomicRanges_1.58.0        GenomeInfoDb_1.42.1         
8000
IRanges_2.40.1              S4Vectors_0.44.0           
[49] BiocGenerics_0.52.0         MatrixGenerics_1.18.1       matrixStats_1.5.0           harmony_1.2.3              
[53] Rcpp_1.0.14                 zellkonverter_1.16.0        Matrix_1.7-2                SeuratDisk_0.0.0.9021      
[57] pbmcref.SeuratData_1.0.0    kidneyref.SeuratData_1.0.2  SeuratData_0.2.2.9001       Seurat_5.2.1               
[61] SeuratObject_5.0.2          sp_2.2-0                   

loaded via a namespace (and not attached):
  [1] SpatialExperiment_1.16.0 goftest_1.2-3            Biostrings_2.74.1        HDF5Array_1.34.0         vctrs_0.6.5             
  [6] spatstat.random_3.3-2    digest_0.6.37            png_0.1-8                shape_1.4.6.1            ggrepel_0.9.6           
 [11] deldir_2.0-4             parallelly_1.42.0        magick_2.8.5             MASS_7.3-64              httpuv_1.6.15           
 [16] foreach_1.5.2            withr_3.0.2              ggrastr_1.0.2            survival_3.8-3           memoise_2.0.1           
 [21] ggbeeswarm_0.7.2         janitor_2.2.1            zoo_1.8-12               GlobalOptions_0.1.2      pbapply_1.7-2           
 [26] GGally_2.2.1             rematch2_2.1.2           KEGGREST_1.46.0          promises_1.3.2           httr_1.4.7              
 [31] globals_0.16.3           fitdistrplus_1.2-2       rhdf5filters_1.18.0      rhdf5_2.50.2             rstudioapi_0.17.1       
 [36] UCSC.utils_1.2.0         miniUI_0.1.1.1           generics_0.1.3           dir.expiry_1.14.0        zlibbioc_1.52.0         
 [41] ScaledMatrix_1.14.0      polyclip_1.10-7          quadprog_1.5-8           GenomeInfoDbData_1.2.13  SparseArray_1.6.1       
 [46] xtable_1.8-4             pracma_2.4.4             doParallel_1.0.17        S4Arrays_1.6.0           hms_1.1.3               
 [51] irlba_2.3.5.1            colorspace_2.1-1         filelock_1.0.3           hdf5r_1.3.12             ROCR_1.0-11             
 [56] spatstat.data_3.1-4      magrittr_2.0.3           lmtest_0.9-40            snakecase_0.11.1         later_1.4.1             
 [61] viridis_0.6.5            lattice_0.22-6           spatstat.geom_3.3-5      future.apply_1.11.3      scattermore_1.2         
 [66] cowplot_1.1.3            RcppAnnoy_0.0.22         pillar_1.10.1            nlme_3.1-167             iterators_1.0.14        
 [71] compiler_4.4.2           beachmat_2.22.0          RSpectra_0.16-2          stringi_1.8.4            tensor_1.5              
 [76] plyr_1.8.9               crayon_1.5.3             abind_1.4-8              ggdendro_0.2.0           gridGraphics_0.5-1      
 [81] locfit_1.5-9.10          graphlayouts_1.2.2       bit_4.5.0.1              fastmatch_1.1-6          codetools_0.2-20        
 [86] BiocSingular_1.22.0      paletteer_1.6.0          GetoptLong_1.0.5         plotly_4.10.4            mime_0.12               
 [91] splines_4.4.2            circlize_0.4.16          fastDummies_1.7.5        basilisk_1.18.0          sparseMatrixStats_1.18.0
 [96] cellranger_1.1.0         blob_1.2.4               clue_0.3-66              fs_1.6.5                 listenv_0.9.1           
[101] ggplotify_0.1.2          statmod_1.5.0            tzdb_0.4.0               tweenr_2.0.3             pkgconfig_2.0.3         
[106] tools_4.4.2              cachem_1.1.0             RSQLite_2.3.9            viridisLite_0.4.2        DBI_1.2.3               
[111] fastmap_1.2.0            scales_1.3.0             ica_1.0-3                ggstats_0.8.0            ggprism_1.0.5           
[116] dotCall64_1.2            RANN_2.6.2               farver_2.1.2             tidygraph_1.3.1          cli_3.6.3               
[121] lifecycle_1.0.4          uwot_0.2.2               mvtnorm_1.3-3            bluster_1.16.0           BiocParallel_1.40.0     
[126] timechange_0.3.0         gtable_0.3.6             rjson_0.2.23             ggridges_0.5.6           progressr_0.15.1        
[131] parallel_4.4.2           limma_3.62.2             jsonlite_1.8.9           edgeR_4.4.1              RcppHNSW_0.6.0          
[136] assertthat_0.2.1         bit64_4.6.0-1            Rtsne_0.17               yulab.utils_0.2.0        spatstat.utils_3.1-2    
[141] BiocNeighbors_2.0.1      metapod_1.14.0           dqrng_0.4.1              spatstat.univar_3.1-1    lazyeval_0.2.2          
[146] shiny_1.10.0             htmltools_0.5.8.1        sctransform_0.4.1        rappdirs_0.3.3           basilisk.utils_1.18.0   
[151] glue_1.8.0               spam_2.11-1              XVector_0.46.0           mclust_6.1.1             ks_1.14.3               
[156] mnormt_2.1.1             SCpubr_2.0.2             gridExtra_2.3            igraph_2.1.4             R6_2.5.1                
[161] labeling_0.4.3           cluster_2.1.8            Rhdf5lib_1.28.0          DelayedArray_0.32.0      tidyselect_1.2.1        
[166] vipor_0.4.7              ggforce_0.4.2            rsvd_1.0.5               munsell_0.5.1            KernSmooth_2.23-24      
[171] htmlwidgets_1.6.4        RColorBrewer_1.1-3       rlang_1.1.5              spatstat.sparse_3.1-0    spatstat.explore_3.3-4  
[176] phangorn_2.12.1          beeswarm_0.4.0
@enblacar
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Owner

Hi @samgest,

First of all, sorry for taking this long to come back to this Issue! And thanks for using my package!

I am in the process of updating SCpubr to a new major version. Would it be possible to get a copy of your de_genes object to debug this issue? You can send it to scpubr@gmail.com.

Thank you!
Enrique

@enblacar
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Owner
enblacar commented May 25, 2025 •
edited
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Hi @samgest,

Thanks for sending the object!

I have pushed a commit that I think could solve the issue (6be4e15). I could not reproduce entirely the error with your de_genes object, so this might need another iteration. If you download this commit and it does still not work, please send me the error log again.

Thanks a lot for helping out with this issue!
Enrique

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