numbers of columns of arguments do not match

[jiangbonong]

when running

res<-scgsva(pbmc,hsko,method="ssgsea")

[1] "Normalizing..."
Error in rbind(deparse.level, ...) :
numbers of columns of arguments do not match
In addition: Warning message:

how to solve this ?
thank you

[adc123456]

same issue for me, I tried to use small batch but no luck.

res<-scgsva(data,hsko,method="ssgsea", batch = 6)

[1] "Normalizing..."
Error in rbind(deparse.level, ...) :
numbers of columns of arguments do not match

[guokai8]

Hi @adc123456 @jiangbonong ,
Could you please provide the R version and the information for the Seurat you used? Maybe just use the sessionInfo()
Thanks!
K

[guokai8]

@adc123456 @jiangbonong, I don't have any issue to run the code:

>      res<-scgsva(pbmc,hsko,batch=6)
Setting parallel calculations through a MulticoreParam back-end
with workers=4 and tasks=100.
Estimating ssGSEA scores for 213 gene sets.
[1] "Calculating ranks..."
[1] "Calculating absolute values from ranks..."
  |======================================================================| 100%

[1] "Normalizing..."
Setting parallel calculations through a MulticoreParam back-end
with workers=4 and tasks=100.
Estimating ssGSEA scores for 211 gene sets.
[1] "Calculating ranks..."
[1] "Calculating absolute values from ranks..."
  |======================================================================| 100%

[1] "Normalizing..."
Setting parallel calculations through a MulticoreParam back-end
with workers=4 and tasks=100.
Estimating ssGSEA scores for 215 gene sets.
[1] "Calculating ranks..."
[1] "Calculating absolute values from ranks..."
  |======================================================================| 100%

[1] "Normalizing..."
Setting parallel calculations through a MulticoreParam back-end
with workers=4 and tasks=100.
Estimating ssGSEA scores for 214 gene sets.
[1] "Calculating ranks..."
[1] "Calculating absolute values from ranks..."
  |======================================================================| 100%

[1] "Normalizing..."
Setting parallel calculations through a MulticoreParam back-end
with workers=4 and tasks=100.
Estimating ssGSEA scores for 216 gene sets.
[1] "Calculating ranks..."
[1] "Calculating absolute values from ranks..."
  |======================================================================| 100%

[1] "Normalizing..."
Setting parallel calculations through a MulticoreParam back-end
with workers=4 and tasks=100.
Estimating ssGSEA scores for 212 gene sets.
[1] "Calculating ranks..."
[1] "Calculating absolute values from ranks..."
  |======================================================================| 100%

[1] "Normalizing..."
Setting parallel calculations through a MulticoreParam back-end
with workers=4 and tasks=100.
Estimating ssGSEA scores for 212 gene sets.
[1] "Calculating ranks..."
[1] "Calculating absolute values from ranks..."
  |======================================================================| 100%

[1] "Normalizing..."
Setting parallel calculations through a MulticoreParam back-end
with workers=4 and tasks=100.
Estimating ssGSEA scores for 212 gene sets.
[1] "Calculating ranks..."
[1] "Calculating absolute values from ranks..."
  |======================================================================| 100%

[1] "Normalizing..."
Setting parallel calculations through a MulticoreParam back-end
with workers=4 and tasks=100.
Estimating ssGSEA scores for 217 gene sets.
[1] "Calculating ranks..."
[1] "Calculating absolute values from ranks..."
  |======================================================================| 100%

[1] "Normalizing..."
Setting parallel calculations through a MulticoreParam back-end
with workers=4 and tasks=100.
Estimating ssGSEA scores for 213 gene sets.
[1] "Calculating ranks..."
[1] "Calculating absolute values from ranks..."
  |======================================================================| 100%

[1] "Normalizing..."
Setting parallel calculations through a MulticoreParam back-end
with workers=4 and tasks=100.
Estimating ssGSEA scores for 211 gene sets.
[1] "Calculating ranks..."
[1] "Calculating absolute values from ranks..."
  |======================================================================| 100%

[1] "Normalizing..."
Setting parallel calculations through a MulticoreParam back-end
with workers=4 and tasks=100.
Estimating ssGSEA scores for 214 gene sets.
[1] "Calculating ranks..."
[1] "Calculating absolute values from ranks..."
  |======================================================================| 100%

[1] "Normalizing..."
Setting parallel calculations through a MulticoreParam back-end
with workers=4 and tasks=100.
Estimating ssGSEA scores for 214 gene sets.
[1] "Calculating ranks..."
[1] "Calculating absolute values from ranks..."
  |======================================================================| 100%

[1] "Normalizing..."
Setting parallel calculations through a MulticoreParam back-end
with workers=4 and tasks=100.
Estimating ssGSEA scores for 211 gene sets.
[1] "Calculating ranks..."
[1] "Calculating absolute values from ranks..."
  |======================================================================| 100%

[1] "Normalizing..."
Setting parallel calculations through a MulticoreParam back-end
with workers=4 and tasks=100.
Estimating ssGSEA scores for 210 gene sets.
[1] "Calculating ranks..."
[1] "Calculating absolute values from ranks..."
  |======================================================================| 100%

[1] "Normalizing..."
Setting parallel calculations through a MulticoreParam back-end
with workers=4 and tasks=100.
Estimating ssGSEA scores for 214 gene sets.
[1] "Calculating ranks..."
[1] "Calculating absolute values from ranks..."
  |======================================================================| 100%

[1] "Normalizing..."
Setting parallel calculations through a MulticoreParam back-end
with workers=4 and tasks=100.
Estimating ssGSEA scores for 212 gene sets.
[1] "Calculating ranks..."
[1] "Calculating absolute values from ranks..."
  |======================================================================| 100%

[1] "Normalizing..."
Setting parallel calculations through a MulticoreParam back-end
with workers=4 and tasks=100.
Estimating ssGSEA scores for 215 gene sets.
[1] "Calculating ranks..."
[1] "Calculating absolute values from ranks..."
  |======================================================================| 100%

[1] "Normalizing..."
Setting parallel calculations through a MulticoreParam back-end
with workers=4 and tasks=100.
Estimating ssGSEA scores for 215 gene sets.
[1] "Calculating ranks..."
[1] "Calculating absolute values from ranks..."
  |======================================================================| 100%

[1] "Normalizing..."
Setting parallel calculations through a MulticoreParam back-end
with workers=4 and tasks=100.
Estimating ssGSEA scores for 215 gene sets.

And here is my environment:

[1] org.Hs.eg.db_3.17.0  AnnotationDbi_1.64.1 IRanges_2.36.0      
[4] S4Vectors_0.40.2     Biobase_2.62.0       BiocGenerics_0.48.1 
[7] SeuratObject_5.0.1   scGSVA_0.0.19       

[adc123456]

Hi @adc123456 @jiangbonong , Could you please provide the R version and the information for the Seurat you used? Maybe just use the sessionInfo() Thanks! K

I changed the method to UCell and it worked.

Here are the session info and error messages below (I only get the error messages after running the normalizing steps for awhile). Thank you!

R version 4.3.1 (2023-06-16 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 11 x64 (build 22631)

Matrix products: default
locale:
[1] LC_COLLATE=English_Canada.utf8  LC_CTYPE=English_Canada.utf8    LC_MONETARY=English_Canada.utf8
[4] LC_NUMERIC=C                    LC_TIME=English_Canada.utf8    

time zone: America/Vancouver
tzcode source: internal

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

other attached packages:
 [1] org.Hs.eg.db_3.17.0  AnnotationDbi_1.62.2 IRanges_2.34.1       S4Vectors_0.38.2     Biobase_2.60.0      
 [6] BiocGenerics_0.46.0  UCell_2.4.0          scGSVA_0.0.20        SeuratObject_4.1.4   Seurat_4.4.0        

loaded via a namespace (and not attached):
  [1] RcppAnnoy_0.0.21            splines_4.3.1               later_1.3.1                
  [4] bitops_1.0-7                tibble_3.2.1                polyclip_1.10-6            
  [7] graph_1.78.0                XML_3.99-0.16.1             lifecycle_1.0.4            
 [10] rstatix_0.7.2               globals_0.16.2              lattice_0.21-8             
 [13] MASS_7.3-60                 backports_1.4.1             magrittr_2.0.3             
 [16] limma_3.56.2                plotly_4.10.4               httpuv_1.6.12              
 [19] sctransform_0.4.1           sp_2.1-3                    spatstat.sparse_3.0-3      
 [22] reticulate_1.34.0           cowplot_1.1.3               pbapply_1.7-2              
 [25] DBI_1.2.1                   RColorBrewer_1.1-3          abind_1.4-5                
 [28] zlibbioc_1.46.0             Rtsne_0.16                  GenomicRanges_1.52.1       
 [31] purrr_1.0.2                 msigdbr_7.5.1               RCurl_1.98-1.14            
 [34] GenomeInfoDbData_1.2.10     ggrepel_0.9.4               irlba_2.3.5.1              
 [37] listenv_0.9.1               spatstat.utils_3.0-4        pheatmap_1.0.12            
 [40] GSVA_1.48.3                 goftest_1.2-3               spatstat.random_3.2-1      
 [43] annotate_1.78.0             fitdistrplus_1.1-11         parallelly_1.36.0          
 [46] DelayedMatrixStats_1.22.6   leiden_0.4.3.1              codetools_0.2-19           
 [49] DelayedArray_0.26.7         tidyselect_1.2.0            farver_2.1.1               
 [52] viridis_0.6.4               ScaledMatrix_1.8.1          matrixStats_1.0.0          
 [55] spatstat.explore_3.2-6      jsonlite_1.8.7              BiocNeighbors_1.18.0       
 [58] ellipsis_0.3.2              progressr_0.14.0            ggridges_0.5.6             
 [61] survival_3.5-5              tools_4.3.1                 ica_1.0-3                  
 [64] Rcpp_1.0.12                 glue_1.6.2                  gridExtra_2.3              
 [67] MatrixGenerics_1.12.3       GenomeInfoDb_1.36.4         dplyr_1.1.3                
 [70] HDF5Array_1.28.1            withr_3.0.0                 fastmap_1.1.1              
 [73] rhdf5filters_1.12.1         fansi_1.0.5                 digest_0.6.34              
 [76] rsvd_1.0.5                  R6_2.5.1                    mime_0.12                  
 [79] colorspace_2.1-0            scattermore_1.2             tensor_1.5                 
 [82] spatstat.data_3.0-4         RSQLite_2.3.5               utf8_1.2.4                 
 [85] tidyr_1.3.0                 generics_0.1.3              data.table_1.14.8          
 [88] httr_1.4.7                  htmlwidgets_1.6.4           S4Arrays_1.0.6             
 [91] uwot_0.1.16                 pkgconfig_2.0.3             gtable_0.3.4               
 [94] blob_1.2.4                  lmtest_0.9-40               SingleCellExperiment_1.22.0
 [97] XVector_0.40.0              htmltools_0.5.7             carData_3.0-5              
[100] fgsea_1.29.1                GSEABase_1.62.0             scales_1.3.0               
[103] png_0.1-8                   rstudioapi_0.15.0           reshape2_1.4.4             
[106] curl_5.2.0                  nlme_3.1-162                cachem_1.0.8               
[109] zoo_1.8-12                  rhdf5_2.44.0                stringr_1.5.1              
[112] KernSmooth_2.23-21          parallel_4.3.1              miniUI_0.1.1.1             
[115] pillar_1.9.0                grid_4.3.1                  vctrs_0.6.4                
[118] RANN_2.6.1                  promises_1.2.1              car_3.1-2                  
[121] BiocSingular_1.16.0         beachmat_2.16.0             xtable_1.8-4               
[124] cluster_2.1.4               cli_3.6.1                   compiler_4.3.1             
[127] rlang_1.1.3                 crayon_1.5.2                future.apply_1.11.1        
[130] labeling_0.4.3              plyr_1.8.9                  stringi_1.7.12             
[133] viridisLite_0.4.2           deldir_1.0-9                BiocParallel_1.34.2        
[136] babelgene_22.9              munsell_0.5.0               Biostrings_2.68.1          
[139] lazyeval_0.2.2              spatstat.geom_3.2-8         Matrix_1.6-5               
[142] patchwork_1.2.0             sparseMatrixStats_1.12.2    bit64_4.0.5                
[145] future_1.33.1               ggplot2_3.4.4               Rhdf5lib_1.22.1            
[148] KEGGREST_1.40.1             shiny_1.8.0                 SummarizedExperiment_1.30.2
[151] ROCR_1.0-11                 broom_1.0.5                 igraph_1.5.1               
[154] memoise_2.0.1               fastmatch_1.1-4             bit_4.0.5                  

[1] "Normalizing..."
Setting parallel calculations through a MulticoreParam back-end
with workers=4 and tasks=100.
Estimating ssGSEA scores for 225 gene sets.
[1] "Calculating ranks..."
[1] "Calculating absolute values from ranks..."
  |===================================================================================================| 100%

[1] "Normalizing..."
Error in rbind(deparse.level, ...) : 
  numbers of columns of arguments do not match
In addition: Warning message:
In asMethod(object) :
  sparse->dense coercion: allocating vector of size 2.9 GiB

[orange-3711]

Hi @guokai8, I had the same problem. I had no problem using buildAnnot's output as input to annot, but I had this error using the self-built annot data frame.

[guokai8]

Hi @adc123456 @orange-3711 @jiangbonong @egeulgen ,
I finally fixed the issue.
K