Cell-level analysis: Vst method

[bassanio]

I have an error while running cell level method

mm <- mmDS(SE, method = "vst", vst = "sctransform")

Error:

Warning: The 'show_progress' argument is deprecated as of v0.3. Use 'verbosity' instead. (in sctransform::vst)
Calculating cell attributes from input UMI matrix: log_umi
Variance stabilizing transformation of count matrix of size 17247 by 17156
Model formula is y ~ log_umi
Get Negative Binomial regression parameters per gene
Using 2000 genes, 17156 cells
  |============================================================================| 100%
Found 124 outliers - those will be ignored in fitting/regularization step

Second step: Get residuals using fitted parameters for 17247 genes
  |============================================================================| 100%
Calculating gene attributes
Wall clock passed: Time difference of 3.924652 mins
Error in `assays<-`(`*tmp*`, withDimnames = withDimnames, ..., value = `*vtmp*`) : 
  please use 'assay(x, withDimnames=FALSE)) <- value' or 'assays(x,
  withDimnames=FALSE)) <- value' when the dimnames on the supplied assay(s)
  are not identical to the dimnames on SingleCellExperiment object 'x'
In addition: There were 50 or more warnings (use warnings() to see the first 50)

SE

class: SingleCellExperiment 
dim: 19304 17156 
metadata(1): experiment_info
assays(2): counts logcounts
rownames(19304): RP11-34P13.7 FO538757.2 ... AP001610.5 LINC01424
rowData names(0):
colnames(17156): AAACCTGAGCTAACTC_1 AAACCTGAGCTCCTCT_1 ...
  AGGGAGTCAGTCGTGC_10 AGGGAGTCATTCCTGC_10
colData names(3): cluster_id sample_id group_id
reducedDimNames(2): REF.SPCA REF.UMAP
altExpNames(0):

[HelenaLC]

Please post the output of your session info.

[bassanio]

sessionInfo()
R version 4.0.4 (2021-02-15)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Big Sur 10.16

Matrix products: default
LAPACK: /Library/Frameworks/R.framework/Versions/4.0/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] parallel  stats4    stats     graphics  grDevices utils     datasets  methods  
[9] base     

other attached packages:
 [1] scater_1.18.6               SingleCellExperiment_1.12.0
 [3] SummarizedExperiment_1.20.0 Biobase_2.50.0             
 [5] GenomicRanges_1.42.0        GenomeInfoDb_1.26.2        
 [7] IRanges_2.24.1              S4Vectors_0.28.1           
 [9] BiocGenerics_0.36.0         MatrixGenerics_1.2.1       
[11] matrixStats_0.58.0          muscat_1.4.0               
[13] ggplot2_3.3.3               cowplot_1.1.1              
[15] RColorBrewer_1.1-2          dplyr_1.0.4                
[17] patchwork_1.1.1             SeuratDisk_0.0.0.9018      
[19] SeuratObject_4.0.0          Seurat_4.0.0               

loaded via a namespace (and not attached):
  [1] utf8_1.1.4                reticulate_1.18           tidyselect_1.1.0         
  [4] lme4_1.1-27.1             RSQLite_2.2.3             AnnotationDbi_1.52.0     
  [7] htmlwidgets_1.5.3         grid_4.0.4                BiocParallel_1.24.1      
 [10] Rtsne_0.15                munsell_0.5.0             codetools_0.2-18         
 [13] ica_1.0-2                 future_1.21.0             miniUI_0.1.1.1           
 [16] withr_2.4.1               colorspace_2.0-0          rstudioapi_0.13          
 [19] ROCR_1.0-11               tensor_1.5                listenv_0.8.0            
 [22] labeling_0.4.2            GenomeInfoDbData_1.2.4    polyclip_1.10-0          
 [25] farver_2.0.3              bit64_4.0.5               glmmTMB_1.1.1            
 [28] parallelly_1.23.0         vctrs_0.3.6               generics_0.1.0           
 [31] doParallel_1.0.16         R6_2.5.0                  ggbeeswarm_0.6.0         
 [34] clue_0.3-58               rsvd_1.0.5                locfit_1.5-9.4           
 [37] hdf5r_1.3.3               bitops_1.0-6              spatstat.utils_2.1-0     
 [40] cachem_1.0.4              DelayedArray_0.16.2       assertthat_0.2.1         
 [43] promises_1.2.0.1          scales_1.1.1              beeswarm_0.2.3           
 [46] gtable_0.3.0              beachmat_2.6.4            Cairo_1.5-12.2           
 [49] globals_0.14.0            goftest_1.2-2             rlang_0.4.10             
 [52] genefilter_1.72.1         GlobalOptions_0.1.2       splines_4.0.4            
 [55] TMB_1.7.20                lazyeval_0.2.2            broom_0.7.7              
 [58] BiocManager_1.30.10       reshape2_1.4.4            abind_1.4-5              
 [61] backports_1.2.1           httpuv_1.5.5              tools_4.0.4              
 [64] gplots_3.1.1              ellipsis_0.3.1            ggridges_0.5.3           
 [67] Rcpp_1.0.6                plyr_1.8.6                sparseMatrixStats_1.2.1  
 [70] progress_1.2.2            zlibbioc_1.36.0           purrr_0.3.4              
 [73] RCurl_1.98-1.2            prettyunits_1.1.1         rpart_4.1-15             
 [76] deldir_0.2-10             viridis_0.5.1             pbapply_1.4-3            
 [79] GetoptLong_1.0.5          zoo_1.8-8                 ggrepel_0.9.1.9999       
 [82] cluster_2.1.1             colorRamps_2.3            variancePartition_1.20.0 
 [85] magrittr_2.0.1            data.table_1.14.0         scattermore_0.7          
 [88] lmerTest_3.1-3            circlize_0.4.12           lmtest_0.9-38            
 [91] RANN_2.6.1                fitdistrplus_1.1-3        hms_1.0.0                
 [94] mime_0.10                 xtable_1.8-4              pbkrtest_0.5.1           
 [97] XML_3.99-0.5              gridExtra_2.3             shape_1.4.5              
[100] compiler_4.0.4            tibble_3.1.0              KernSmooth_2.23-18       
[103] crayon_1.4.1              minqa_1.2.4               htmltools_0.5.1.1        
[106] mgcv_1.8-34               later_1.1.0.1             tidyr_1.1.2              
[109] geneplotter_1.68.0        DBI_1.1.1                 ComplexHeatmap_2.6.2     
[112] MASS_7.3-53.1             boot_1.3-27               Matrix_1.3-2             
[115] cli_2.3.1                 igraph_1.2.6              pkgconfig_2.0.3          
[118] numDeriv_2016.8-1.1       plotly_4.9.3              scuttle_1.0.4            
[121] foreach_1.5.1             annotate_1.68.0           vipor_0.4.5              
[124] blme_1.0-5                XVector_0.30.0            stringr_1.4.0            
[127] digest_0.6.27             sctransform_0.3.2         RcppAnnoy_0.0.18         
[130] spatstat.data_2.1-0       leiden_0.3.7              uwot_0.1.10              
[133] edgeR_3.32.1              DelayedMatrixStats_1.12.3 gtools_3.8.2             
[136] shiny_1.6.0               rjson_0.2.20              nloptr_1.2.2.2           
[139] lifecycle_1.0.0           nlme_3.1-152              jsonlite_1.7.2           
[142] BiocNeighbors_1.8.2       viridisLite_0.3.0         limma_3.46.0             
[145] fansi_0.4.2               pillar_1.5.0              lattice_0.20-41          
[148] fastmap_1.1.0             httr_1.4.2                survival_3.2-7           
[151] glue_1.4.2                remotes_2.2.0             spatstat_1.64-1          
[154] iterators_1.0.13          png_0.1-7                 bit_4.0.4                
[157] stringi_1.5.3             blob_1.2.1                DESeq2_1.30.1            
[160] BiocSingular_1.6.0        caTools_1.18.1            memoise_2.0.0            
[163] irlba_2.3.3               future.apply_1.7.0       

[bassanio]

Hi,

Any update on this issue

[HelenaLC]

My apologies, this slipped under my radar, thanks for the reminder!

Have you attempted using another method in mmDS(), i.e., is this issue specific to "vst" or general?

In other news: The current Bioc release version of muscat is 1.6.0, using R v4.1. I highly recommend keeping up to date with the release cycles, as all of Bioc is under continuous development and issues might be resolved automatically in the process.

In fact, I believe this should be resolved according to the current code where

# variance-stabilizing transformation
if (args$method == "vst" && !"vstresiduals" %in% assayNames(x)) {
    vst_call <- switch(args$vst,
        sctransform = expression(.vst_sctransform(x, verbose)),
        DESeq2 = expression(.vst_DESeq2(x, covs, blind)))
    if (verbose) {
        assay(x, "vstresiduals", FALSE) <- eval(vst_call)
    } else {
        assay(x, "vstresiduals", FALSE) <- suppressMessages(eval(vst_call))
    }
}

The error you posted would indicate the assay assignment was done as assay(object, "name") <- matrix. But the current version uses assay(object, "name", withDimnames = FALSE) <- matrix, which should not give the above error.