Error in SCTransform (useNames = NA is defunct. Instead, specify either useNames = TRUE or useNames = FALSE) Related to Closed Issue #7501

[AndrewHardigan]

Hello,

I am getting an error message (not a warning) running SCTransform() that prevents further analyses of the RNA/SCT (using the WNN analysis of 10x Multiome, RNA + ATAC Vignette as a guide)

This issue was previously discussed (#7501 ) as the same message was seen as a "warning" but not an "error" when running SCTransform, however that issue was closed as completed on July 6th, so I am posting a new issue here ( I originally posted to that issue before seeing it was closed).

Project: 10X Multiome dataset 11,775 nuclei/barcodes after filtering using WNN as a guide.

My code was multiome <- SCTransform(multiome, verbose = FALSE) %>% RunPCA() %>% RunUMAP(dims = 1:50, reduction.name = 'umap.rna', reduction.key = 'rnaUMAP_')

Which returned: Error: useNames = NA is defunct. Instead, specify either useNames = TRUE or useNames = FALSE.

To narrow down which command prompted this error, I started again and it occurs during the SCTransform call:

DefaultAssay(multiome) <- "RNA"
multiome <- SCTransform(multiome, verbose = FALSE)
Error: useNames = NA is defunct. Instead, specify either useNames = TRUE or useNames = FALSE.

I first ran the 10k PBMC Multiome WNN Vignette code (copied below) yesterday without issue, however strangely I now also get the same error when I run the same code:

setwd("10X_Test_Data_Seurat_Vignette/")
rm(list=ls())
library(Seurat)
library(Signac)
library(EnsDb.Hsapiens.v86)
library(dplyr)
library(ggplot2)

# the 10x hdf5 file contains both data types. 
inputdata.10x <- Read10X_h5("pbmc_granulocyte_sorted_10k_filtered_feature_bc_matrix.h5")

# extract RNA and ATAC data
rna_counts <- inputdata.10x$`Gene Expression`
atac_counts <- inputdata.10x$Peaks

# Create Seurat object
pbmc <- CreateSeuratObject(counts = rna_counts)
pbmc[["percent.mt"]] <- PercentageFeatureSet(pbmc, pattern = "^MT-")

# Now add in the ATAC-seq data
# we'll only use peaks in standard chromosomes
length(rownames(atac_counts))
grange.counts <- StringToGRanges(rownames(atac_counts), sep = c(":", "-"))
grange.use <- seqnames(grange.counts) %in% standardChromosomes(grange.counts)
atac_counts <- atac_counts[as.vector(grange.use), ]
annotations <- GetGRangesFromEnsDb(ensdb = EnsDb.Hsapiens.v86)
warnings()
seqlevelsStyle(annotations) <- 'UCSC'
genome(annotations) <- "hg38"

frag.file <- "pbmc_granulocyte_sorted_10k_atac_fragments.tsv.gz"
chrom_assay <- CreateChromatinAssay(
  counts = atac_counts,
  sep = c(":", "-"),
  genome = 'hg38',
  fragments = frag.file,
  min.cells = 10,
  annotation = annotations
)
pbmc[["ATAC"]] <- chrom_assay

#We perform basic QC based on the number of detected molecules for each modality as well as mitochondrial percentage.

VlnPlot(pbmc, features = c("nCount_ATAC", "nCount_RNA", "percent.mt"), ncol = 3,
        log = TRUE, pt.size = 0) + NoLegend()

#Vlnplots here

pbmc <- subset(
  x = pbmc,
  subset = nCount_ATAC < 7e4 &
    nCount_ATAC > 5e3 &
    nCount_RNA < 25000 &
    nCount_RNA > 1000 &
    percent.mt < 20
)

#We next perform pre-processing and dimensional reduction on both assays independently, using standard approaches for RNA and ATAC-seq data.

# RNA analysis
DefaultAssay(pbmc) <- "RNA"
pbmc <- SCTransform(pbmc, verbose = FALSE) %>% RunPCA() %>% RunUMAP(dims = 1:50, reduction.name = 'umap.rna', reduction.key = 'rnaUMAP_')

Error: useNames = NA is defunct. Instead, specify either useNames = TRUE or useNames = FALSE.
`

Attempting to specify useNames = TRUE or useNames = FALSE per the error message also does not work, and both attempts yield the same error:

`> pbmc <- SCTransform(pbmc, verbose = FALSE, useNames=TRUE)
Error in vst(useNames = TRUE, vst.flavor = "v2", umi = new("dgCMatrix",  : 
  unused argument (useNames = TRUE)
> pbmc <- SCTransform(pbmc, verbose = FALSE, useNames=FALSE)
Error in vst(useNames = FALSE, vst.flavor = "v2", umi = new("dgCMatrix",  : 
  unused argument (useNames = FALSE)`

I do not recall updating or changing any packages since running this code yesterday that would explain this change.

Thank you for your help with this issue!

`> sessionInfo()
R version 4.2.2 (2022-10-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 22.04.1 LTS

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               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    LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C             LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

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

other attached packages:
 [1] ggpubr_0.6.0              ggplot2_3.4.4             EnsDb.Hsapiens.v86_2.99.0 ensembldb_2.22.0         
 [5] AnnotationFilter_1.22.0   GenomicFeatures_1.50.3    AnnotationDbi_1.60.2      Biobase_2.58.0           
 [9] GenomicRanges_1.50.2      GenomeInfoDb_1.34.9       IRanges_2.32.0            S4Vectors_0.36.2         
[13] BiocGenerics_0.44.0       Signac_1.12.0             dplyr_1.1.4               cowplot_1.1.1            
[17] bmcite.SeuratData_0.3.0   SeuratData_0.2.2.9001     Seurat_5.0.1              SeuratObject_5.0.1       
[21] sp_2.1-2                 

loaded via a namespace (and not attached):
  [1] rappdirs_0.3.3              rtracklayer_1.58.0          scattermore_1.2             R.methodsS3_1.8.2          
  [5] tidyr_1.3.0                 bit64_4.0.5                 knitr_1.45                  irlba_2.3.5.1              
  [9] DelayedArray_0.24.0         R.utils_2.12.2              data.table_1.14.10          rpart_4.1.19               
 [13] KEGGREST_1.38.0             RCurl_1.98-1.13             generics_0.1.3              callr_3.7.3                
 [17] usethis_2.1.6               RSQLite_2.3.4               RANN_2.6.1                  future_1.33.0              
 [21] bit_4.0.5                   spatstat.data_3.0-3         xml2_1.3.3                  httpuv_1.6.13              
 [25] SummarizedExperiment_1.28.0 assertthat_0.2.1            xfun_0.41                   hms_1.1.3                  
 [29] evaluate_0.23               promises_1.2.1              fansi_1.0.6                 restfulr_0.0.15            
 [33] progress_1.2.2              dbplyr_2.3.0                igraph_1.6.0                DBI_1.1.3                  
 [37] htmlwidgets_1.6.4           spatstat.geom_3.2-7         purrr_1.0.2                 ellipsis_0.3.2             
 [41] RSpectra_0.16-1             backports_1.4.1             sparseMatrixStats_1.10.0    biomaRt_2.54.1             
 [45] deldir_2.0-2                MatrixGenerics_1.10.0       vctrs_0.6.5                 remotes_2.4.2              
 [49] ROCR_1.0-11                 abind_1.4-5                 cachem_1.0.8                withr_2.5.2                
 [53] BSgenome_1.66.3             progressr_0.14.0            presto_1.0.0                checkmate_2.3.1            
 [57] sctransform_0.4.1           GenomicAlignments_1.34.1    prettyunits_1.2.0           goftest_1.2-3              
 [61] cluster_2.1.4               dotCall64_1.1-1             lazyeval_0.2.2              crayon_1.5.2               
 [65] hdf5r_1.3.8                 spatstat.explore_3.2-5      pkgconfig_2.0.3             vipor_0.4.5                
 [69] nlme_3.1-161                pkgload_1.3.2               ProtGenerics_1.30.0         nnet_7.3-18                
 [73] devtools_2.4.5              rlang_1.1.2                 globals_0.16.2              lifecycle_1.0.4            
 [77] miniUI_0.1.1.1              filelock_1.0.2              fastDummies_1.7.3           BiocFileCache_2.6.0        
 [81] dichromat_2.0-0.1           ggrastr_1.0.2               polyclip_1.10-6             RcppHNSW_0.5.0             
 [85] matrixStats_1.2.0           lmtest_0.9-40               Matrix_1.6-4                carData_3.0-5              
 [89] zoo_1.8-11                  beeswarm_0.4.0              base64enc_0.1-3             ggridges_0.5.4             
 [93] processx_3.8.0              png_0.1-8                   viridisLite_0.4.2           rjson_0.2.21               
 [97] bitops_1.0-7                R.oo_1.25.0                 KernSmooth_2.23-20          spam_2.10-0                
[101] Biostrings_2.66.0           DelayedMatrixStats_1.20.0   blob_1.2.4                  stringr_1.5.1              
[105] parallelly_1.36.0           spatstat.random_3.2-2       rstatix_0.7.2               ggsignif_0.6.4             
[109] scales_1.3.0                memoise_2.0.1               magrittr_2.0.3              plyr_1.8.9                 
[113] ica_1.0-3                   zlibbioc_1.44.0             compiler_4.2.2              BiocIO_1.8.0               
[117] RColorBrewer_1.1-3          fitdistrplus_1.1-11         Rsamtools_2.14.0            cli_3.6.2                  
[121] XVector_0.38.0              urlchecker_1.0.1            listenv_0.9.0               patchwork_1.1.3            
[125] pbapply_1.7-2               ps_1.7.2                    htmlTable_2.4.2             Formula_1.2-5              
[129] MASS_7.3-58.1               tidyselect_1.2.0            stringi_1.8.3               glmGamPoi_1.10.2           
[133] yaml_2.3.8                  ggrepel_0.9.4               grid_4.2.2                  VariantAnnotation_1.44.1   
[137] fastmatch_1.1-4             tools_4.2.2                 future.apply_1.11.0         parallel_4.2.2             
[141] rstudioapi_0.14             foreign_0.8-84              gridExtra_2.3               farver_2.1.1               
[145] Rtsne_0.17                  digest_0.6.33               BiocManager_1.30.19         shiny_1.8.0                
[149] Rcpp_1.0.11                 car_3.1-2                   broom_1.0.5                 later_1.3.2                
[153] RcppAnnoy_0.0.21            httr_1.4.7                  biovizBase_1.46.0           colorspace_2.1-0           
[157] XML_3.99-0.16               fs_1.6.3                    tensor_1.5                  reticulate_1.34.0          
[161] splines_4.2.2               uwot_0.1.16                 RcppRoll_0.3.0              spatstat.utils_3.0-4       
[165] plotly_4.10.3               sessioninfo_1.2.2           xtable_1.8-4                jsonlite_1.8.8             
[169] R6_2.5.1                    profvis_0.3.7               Hmisc_5.1-1                 pillar_1.9.0               
[173] htmltools_0.5.7             mime_0.12                   glue_1.6.2                  fastmap_1.1.1              
[177] BiocParallel_1.32.6         codetools_0.2-18            pkgbuild_1.4.0              utf8_1.2.4                 
[181] lattice_0.20-45             spatstat.sparse_3.0-3       tibble_3.2.1                ggbeeswarm_0.7.2           
[185] curl_5.2.0                  leiden_0.4.3.1              survival_3.5-0              rmarkdown_2.25             
[189] munsell_0.5.0               GenomeInfoDbData_1.2.9      reshape2_1.4.4              gtable_0.3.4    `

[saketkc]

Does this workaround work for you?

[AndrewHardigan]

Hi Saket,

I can confirm that removing matrixStats and following your above fix in the other issue thread to install matrixStats version 1.1.0 has fixed this issue.

Thank you very much for your help! (and especially for being so quick with the fix!)

Best regards

-Drew

[saketkc]

Hi @AndrewHardigan, On digging deeper, this seems to be coming from glmGamPoi. My recommendation would be to update to latest Bioconductor:

BiocManager::install(version = "3.18")

which should fix everything (even if you have matrixStats 1.2)

[hezuoxi]

downgrade matrixStats also works for me

[ArzooShamoon]

Hi, I tried the above suggestions but still facing the issue while running singleR. Can you please help me to resolve the error. ref <- celldex::HumanPrimaryCellAtlasData() colData(ref) results <- SingleR (test = as.SingleCellExperiment(Sample.combined), ref = ref, labels = ref$label.main, useNames = TRUE) results

Error: useNames = NA is defunct. Instead, specify either useNames = TRUE or useNames = FALSE. Traceback:

1. SingleR(test = as.SingleCellExperiment(Sample.combined), ref = ref, . labels = ref$label.main)
2. trainSingleR(ref, labels, genes = genes, sd.thresh = sd.thresh, . de.method = de.method, de.n = de.n, de.args = de.args, aggr.ref = aggr.ref, . aggr.args = aggr.args, recompute = recompute, restrict = restrict, . check.missing = FALSE, BNPARAM = BNPARAM, num.threads = num.threads, . BPPARAM = BPPARAM)
3. mapply(FUN = .identify_genes, ref = ref, labels = labels, genes = genes, . MoreArgs = list(de.method = de.method, de.n = de.n, de.args = de.args, . BPPARAM = BPPARAM), SIMPLIFY = FALSE)
4. (function (ref, labels, genes = "de", de.method = "classic", . de.n = NULL, de.args = list(), BPPARAM = BPPARAM) . { . if (length(labels) != ncol(ref)) { . stop("number of labels must be equal to number of cells") . } . if (.is_list(genes)) { . is.char <- vapply(genes, is.character, TRUE) . if (all(is.char)) { . genes <- .convert_per_label_set(genes) . } . else if (any(is.char)) { ...
5. matrixStats::rowMedians(x, rows = rows, cols = cols, na.rm = na.rm, . dim. = dim., ..., useNames = useNames)
6. deprecatedUseNamesNA()
7. .Defunct(msg = "useNames = NA is defunct. Instead, specify either useNames = TRUE or useNames = FALSE.", . package = .packageName)

packageVersion("matrixStats") [1] ‘1.1.0’ packageVersion("BiocManager") [1] ‘1.30.22’

[kayihui]

I got the same error code working with Single R, and downgrade matrixStats doesn't work for me.

[ArzooShamoon]

I tried to update the matrixStats package, and everything was resolved while running a single R package.

[kayihui]

I tried to update the matrixStats package, and everything was resolved while running a single R package.

Update to which version of matrixStats?

Thank you

[ArzooShamoon]

[1] sessioninfo_1.2.2 viridis_0.6.5
[3] viridisLite_0.4.2 scRNAseq_2.12.0
[5] SingleCellExperiment_1.20.1 textshaping_0.3.7
[7] EnhancedVolcano_1.16.0 ggrepel_0.9.5
[9] magrittr_2.0.3 tidyr_1.3.1
[11] wrapr_2.1.0 celldex_1.8.0
[13] SingleR_2.0.0 SummarizedExperiment_1.28.0
[15] Biobase_2.58.0 GenomicRanges_1.50.2
[17] GenomeInfoDb_1.34.9 IRanges_2.32.0
[19] S4Vectors_0.36.2 BiocGenerics_0.44.0
[21] MatrixGenerics_1.10.0 matrixStats_1.1.0
[23] bonemarrowref.SeuratData_1.0.0 SeuratData_0.2.2.9001
[25] RColorBrewer_1.1-3 ggplot2_3.5.0
[27] patchwork_1.2.0 Seurat_5.0.0
[29] SeuratObject_5.0.1 sp_2.1-4
[31] dplyr_1.1.4

After installing the specific package version, close and restart RStudio to ensure the changes take effect.

[kayihui]

hi there,

Thank you for your reply.

I still got a warning message.

Warning: useNames = NA is deprecated. Instead, specify either useNames = TRUE or useNames = FALSE.

But the function SingleR did return the results, so it looks like it worked. Do you still see the warning message?