Error when running "ModuleEigengenes()" with a seurat.v5 object

[Zweig-Wong]

When running ModuleEigengenes() with a seurat.v5 object I got an error:

Error in `LayerData<-`:
! 'layer' must be a single non-empty string

It can be traced back to SetAssayData() in ComputeModuleEigengene

Backtrace:
    ▆
 1. └─hdWGCNA::ModuleEigengenes(...)
 2.   └─hdWGCNA:::ComputeModuleEigengene(...)
 3.     ├─SeuratObject::SetAssayData(...) at <tmp>:27:9
 4.     └─SeuratObject:::SetAssayData.Seurat(...)
 5.       ├─SeuratObject::SetAssayData(...)
 6.       └─SeuratObject:::SetAssayData.StdAssay(...)
 7.         ├─SeuratObject::`LayerData<-`(object = `*tmp*`, layer = slot, value = new.data)
 8.         └─SeuratObject:::`LayerData<-.Assay5`(object = `*tmp*`, layer = slot, value = new.data)
 9.           └─rlang::abort(message = "'layer' must be a single non-empty string")

Steps to reproduce

NPC <- ModuleEigengenes(NPC, group.by.vars = "orig.ident")

R session info

> sessionInfo()
R version 4.3.2 (2023-10-31)
Platform: x86_64-conda-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

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

time zone: Asia/Shanghai
tzcode source: system (glibc)

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

other attached packages:
 [1] hdWGCNA_0.3.02        igraph_1.5.1          WGCNA_1.71           
 [4] fastcluster_1.2.3     dynamicTreeCut_1.63-1 ggrepel_0.9.4        
 [7] harmony_1.2.0         Rcpp_1.0.11           future_1.33.0        
[10] ggalluvial_0.12.5     ggpubr_0.6.0          clustree_0.5.1       
[13] ggraph_2.1.0          patchwork_1.2.0       Seurat_5.0.3         
[16] SeuratObject_5.0.0    sp_2.1-2              this.path_2.3.0      
[19] vroom_1.6.4           data.table_1.14.8     lubridate_1.9.3      
[22] forcats_1.0.0         stringr_1.5.1         dplyr_1.1.3          
[25] purrr_1.0.2           readr_2.1.4           tidyr_1.3.0          
[28] tibble_3.2.1          ggplot2_3.4.4         tidyverse_2.0.0      

loaded via a namespace (and not attached):
  [1] RcppAnnoy_0.0.21        splines_4.3.2           later_1.3.2            
  [4] bitops_1.0-7            polyclip_1.10-6         preprocessCore_1.64.0  
  [7] rpart_4.1.23            fastDummies_1.7.3       lifecycle_1.0.4        
 [10] rstatix_0.7.2           doParallel_1.0.17       globals_0.16.2         
 [13] lattice_0.22-5          MASS_7.3-60             backports_1.4.1        
 [16] magrittr_2.0.3          rmarkdown_2.25          Hmisc_5.1-1            
 [19] plotly_4.10.4           httpuv_1.6.13           sctransform_0.4.1      
 [22] spam_2.10-0             spatstat.sparse_3.0-3   reticulate_1.34.0      
 [25] cowplot_1.1.1           pbapply_1.7-2           DBI_1.1.3              
 [28] RColorBrewer_1.1-3      zlibbioc_1.48.0         abind_1.4-5            
 [31] Rtsne_0.17              RCurl_1.98-1.12         BiocGenerics_0.48.1    
 [34] nnet_7.3-19             tweenr_2.0.3            GenomeInfoDbData_1.2.11
 [37] IRanges_2.36.0          S4Vectors_0.40.2        irlba_2.3.5.1          
 [40] listenv_0.9.0           spatstat.utils_3.0-4    goftest_1.2-3          
 [43] RSpectra_0.16-1         spatstat.random_3.2-3   fitdistrplus_1.1-11    
 [46] parallelly_1.36.0       leiden_0.4.3.1          codetools_0.2-19       
 [49] ggforce_0.4.2           tidyselect_1.2.0        farver_2.1.1           
 [52] tester_0.2.0            viridis_0.6.5           base64enc_0.1-3        
 [55] matrixStats_1.0.0       stats4_4.3.2            spatstat.explore_3.2-6 
 [58] jsonlite_1.8.8          Formula_1.2-5           ellipsis_0.3.2         
 [61] tidygraph_1.3.0         progressr_0.14.0        ggridges_0.5.6         
 [64] survival_3.5-7          iterators_1.0.14        foreach_1.5.2          
 [67] ica_1.0-3               glue_1.6.2              gridExtra_2.3          
 [70] xfun_0.41               GenomeInfoDb_1.38.1     withr_2.5.2            
 [73] fastmap_1.1.1           fansi_1.0.6             digest_0.6.33          
 [76] timechange_0.2.0        R6_2.5.1                mime_0.12              
 [79] colorspace_2.1-0        scattermore_1.2         GO.db_3.18.0           
 [82] tensor_1.5              spatstat.data_3.0-4     RSQLite_2.3.1          
 [85] utf8_1.2.4              generics_0.1.3          FNN_1.1.3.2            
 [88] graphlayouts_1.1.0      httr_1.4.7              htmlwidgets_1.6.4      
 [91] uwot_0.1.16             pkgconfig_2.0.3         gtable_0.3.4           
 [94] blob_1.2.4              impute_1.76.0           lmtest_0.9-40          
 [97] XVector_0.42.0          htmltools_0.5.7         carData_3.0-5          
[100] dotCall64_1.1-1         scales_1.2.1            Biobase_2.62.0         
[103] png_0.1-8               rstudioapi_0.15.0       knitr_1.45             
[106] tzdb_0.4.0              reshape2_1.4.4          checkmate_2.3.0        
[109] nlme_3.1-163            proxy_0.4-27            zoo_1.8-12             
[112] cachem_1.0.8            KernSmooth_2.23-22      parallel_4.3.2         
[115] miniUI_0.1.1.1          foreign_0.8-86          AnnotationDbi_1.64.1   
[118] pillar_1.9.0            grid_4.3.2              vctrs_0.6.5            
[121] RANN_2.6.1              promises_1.2.1          car_3.1-2              
[124] xtable_1.8-4            cluster_2.1.6           htmlTable_2.4.1        
[127] evaluate_0.23           cli_3.6.1               compiler_4.3.2         
[130] rlang_1.1.2             crayon_1.5.2            future.apply_1.11.0    
[133] ggsignif_0.6.4          labeling_0.4.3          plyr_1.8.9             
[136] stringi_1.8.2           viridisLite_0.4.2       deldir_2.0-4           
[139] munsell_0.5.0           Biostrings_2.70.1       lazyeval_0.2.2         
[142] spatstat.geom_3.2-9     pacman_0.5.1            Matrix_1.6-1.1         
[145] RcppHNSW_0.6.0          hms_1.1.3               bit64_4.0.5            
[148] KEGGREST_1.42.0         shiny_1.8.0             ROCR_1.0-11            
[151] broom_1.0.5             memoise_2.0.1           bit_4.0.5 

Screenshots

I would appreciate it if you could address this problem. Thanks.

[Zweig-Wong]

I thought I found the way to fix it:

Just use the old arg "slot" instead of the new one "layer".

[smorabit]

Hi, I am unfortunately not able to reproduce your error. Is this problem specific to your dataset, or does it happen on any dataset that you use like the tutorial dataset?

[Zweig-Wong]

Hi, I am unfortunately not able to reproduce your error. Is this problem specific to your dataset, or does it happen on any dataset that you use like the tutorial dataset?

Thanks for your reply! I haven't tried other datasets yet, but my data was updated from a seurat v4 object using UpdateSeuratObject(). I wonder whether there are some compatibility issues relating to the update...? But changing the layer to slot in that line did work for my data. If this problem does not happen on other data, maybe it's not a big deal? Anyway, currently it works just fine. Thanks a lot for developing this creative algorithm!

[smorabit]

Okay that is interesting, I have tested hdWGCNA successfully with Seurat v4 and Seurat v5 objects, but I have not tried using UpdateSeuratObject, so maybe the issue is related to how the data is re-formatted with that function. I will perform some additional testing to see if I can reproduce the issue.

[CWYuan08]

Dear @smorabit @Zweig-Wong @samuel-marsh @rootze
I am encountering a similar error,

seurat_obj <- SetDatExpr(

• seurat_obj,
• group_name = "24",
• group.by = 'seurat_clusters',
• assay = 'SCT',
• slot = 'data'
• )
  Error in dim(X) <- c(n, length(X)/n) :
  dims [product 0] do not match the length of object [479]
  In addition: Warning message:
  Layer 'data' is empty

I checked layer 'data' is not empty and I am running with seurat V5.
Do you have any idea on how to debug this?

Thank you very much!
CW