Error in SingleR when using scRNAseq dataset : number of labels must be equal to number of cells
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Entering edit mode
3 months ago
Candice • 0

Hi, I am trying to load the scRNAseq package WuKidneyData() to perform the SingleR function to annotate my single-cell data pbmc.1k.sce

library(scRNAseq)
WuKidney.data <- WuKidneyData(ensembl = FALSE)

Due the lack of logcounts in assay(), I have to create one on my own:

counts <- assay(WuKidney.data, "counts")
libsizes <- colSums(counts)
size.factors <- libsizes/mean(libsizes)
logcounts(WuKidney.data) <- log2(t(t(counts)/size.factors) + 1)

In addition, I need to capitalize the gene ID:

rownames(WuKidney.data) <- toupper(rownames(WuKidney.data)) 

However, when I run 'SingleR()', I ran into an error message:

prediction <- SingleR(test=pbmc.1k.sce, assay.type.test=1, 
                               ref=WuKidney.data, labels=WuKidney.data$label.main)

Error in (function (ref, labels, genes = "de", sd.thresh = 1, de.method = "classic",  : 
      number of labels must be equal to number of cells

Please let me know how could I fix it. Thank you!

Session info:

R version 4.0.2 (2020-06-22)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Catalina 10.15.7

Matrix products: default
BLAS:   /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
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   base     

other attached packages:
 [1] scRNAseq_2.4.0              DT_0.20                     R2HTML_2.3.2               
 [4] rjson_0.2.21                scales_1.1.1                Matrix_1.4-0               
 [7] SeuratObject_4.0.4          Seurat_4.0.1                forcats_0.5.1              
[10] stringr_1.4.0               dplyr_1.0.7                 purrr_0.3.4                
[13] readr_2.1.1                 tidyr_1.1.4                 tibble_3.1.6               
[16] tidyverse_1.3.1             pheatmap_1.0.12             celldex_1.0.0              
[19] SingleR_1.4.1               cellassign_0.99.21          tensorflow_2.7.0           
[22] DropletUtils_1.10.3         scran_1.18.7                scater_1.18.6              
[25] ggplot2_3.3.5               SingleCellExperiment_1.12.0 SummarizedExperiment_1.20.0
[28] Biobase_2.50.0              GenomicRanges_1.42.0        GenomeInfoDb_1.26.7        
[31] IRanges_2.24.1              S4Vectors_0.28.1            BiocGenerics_0.36.1        
[34] MatrixGenerics_1.2.1        matrixStats_0.61.0         

loaded via a namespace (and not attached):
  [1] rappdirs_0.3.3                rtracklayer_1.50.0            scattermore_0.7              
  [4] R.methodsS3_1.8.1             bit64_4.0.5                   irlba_2.3.5                  
  [7] DelayedArray_0.16.3           R.utils_2.11.0                data.table_1.14.2            
 [10] rpart_4.1-15                  AnnotationFilter_1.14.0       RCurl_1.98-1.5               
 [13] generics_0.1.1                GenomicFeatures_1.42.3        cowplot_1.1.1                
 [16] RSQLite_2.2.9                 RANN_2.6.1                    future_1.23.0                
 [19] bit_4.0.4                     tzdb_0.2.0                    spatstat.data_2.1-2          
 [22] xml2_1.3.3                    lubridate_1.8.0               httpuv_1.6.5                 
 [25] assertthat_0.2.1              viridis_0.6.2                 xfun_0.29                    
 [28] jquerylib_0.1.4               hms_1.1.1                     promises_1.2.0.1             
 [31] progress_1.2.2                fansi_1.0.2                   dbplyr_2.1.1                 
 [34] readxl_1.3.1                  igraph_1.2.6                  DBI_1.1.2                    
 [37] htmlwidgets_1.5.4             spatstat.geom_2.3-1           ellipsis_0.3.2               
 [40] crosstalk_1.2.0               RSpectra_0.16-0               backports_1.4.1              
 [43] biomaRt_2.46.3                deldir_1.0-6                  sparseMatrixStats_1.2.1      
 [46] vctrs_0.3.8                   ensembldb_2.14.1              here_1.0.1                   
 [49] ROCR_1.0-11                   abind_1.4-5                   cachem_1.0.6                 
 [52] withr_2.4.3                   vroom_1.5.7                   sctransform_0.3.2            
 [55] GenomicAlignments_1.26.0      prettyunits_1.1.1             goftest_1.2-3                
 [58] cluster_2.1.2                 ExperimentHub_1.16.1          lazyeval_0.2.2               
 [61] crayon_1.4.2                  edgeR_3.32.1                  pkgconfig_2.0.3              
 [64] labeling_0.4.2                ProtGenerics_1.22.0           nlme_3.1-152                 
 [67] vipor_0.4.5                   rlang_0.4.12                  globals_0.14.0               
 [70] lifecycle_1.0.1               miniUI_0.1.1.1                BiocFileCache_1.14.0         
 [73] modelr_0.1.8                  rsvd_1.0.5                    AnnotationHub_2.22.1         
 [76] cellranger_1.1.0              rprojroot_2.0.2               polyclip_1.10-0              
 [79] lmtest_0.9-39                 Rhdf5lib_1.12.1               zoo_1.8-9                    
 [82] reprex_2.0.1                  base64enc_0.1-3               beeswarm_0.4.0               
 [85] whisker_0.4                   ggridges_0.5.3                png_0.1-7                    
 [88] viridisLite_0.4.0             bitops_1.0-7                  R.oo_1.24.0                  
 [91] KernSmooth_2.23-20            rhdf5filters_1.2.1            Biostrings_2.58.0            
 [94] blob_1.2.2                    DelayedMatrixStats_1.12.3     parallelly_1.30.0            
 [97] beachmat_2.6.4                memoise_2.0.1                 magrittr_2.0.1               
[100] plyr_1.8.6                    ica_1.0-2                     zlibbioc_1.36.0              
[103] compiler_4.0.2                dqrng_0.3.0                   tinytex_0.36                 
[106] RColorBrewer_1.1-2            fitdistrplus_1.1-6            Rsamtools_2.6.0              
[109] cli_3.1.0                     XVector_0.30.0                listenv_0.8.0                
[112] patchwork_1.1.1               pbapply_1.5-0                 MASS_7.3-55                  
[115] mgcv_1.8-38                   tidyselect_1.1.1              stringi_1.7.6                
[118] yaml_2.2.1                    askpass_1.1                   BiocSingular_1.6.0           
[121] locfit_1.5-9.4                ggrepel_0.9.1                 grid_4.0.2                   
[124] sass_0.4.0                    tools_4.0.2                   future.apply_1.8.1           
[127] rstudioapi_0.13               bluster_1.0.0                 gridExtra_2.3                
[130] farver_2.1.0                  Rtsne_0.15                    digest_0.6.29                
[133] BiocManager_1.30.16           shiny_1.7.1                   Rcpp_1.0.8                   
[136] broom_0.7.11                  scuttle_1.0.4                 BiocVersion_3.12.0           
[139] later_1.3.0                   RcppAnnoy_0.0.19              httr_1.4.2                   
[142] AnnotationDbi_1.52.0          colorspace_2.0-2              XML_3.99-0.8                 
[145] rvest_1.0.2                   fs_1.5.2                      tensor_1.5                   
[148] reticulate_1.23               splines_4.0.2                 uwot_0.1.11                  
[151] statmod_1.4.36                spatstat.utils_2.3-0          plotly_4.10.0                
[154] xtable_1.8-4                  jsonlite_1.7.2                R6_2.5.1                     
[157] pillar_1.6.4                  htmltools_0.5.2               mime_0.12                    
[160] glue_1.6.0                    fastmap_1.1.0                 BiocParallel_1.24.1          
[163] BiocNeighbors_1.8.2           interactiveDisplayBase_1.28.0 codetools_0.2-18             
[166] utf8_1.2.2                    bslib_0.3.1                   lattice_0.20-45              
[169] spatstat.sparse_2.1-0         curl_4.3.2                    ggbeeswarm_0.6.0             
[172] leiden_0.3.9                  tfruns_1.5.0                  openssl_1.4.6                
[175] survival_3.2-13               limma_3.46.0                  munsell_0.5.0                
[178] rhdf5_2.34.0                  GenomeInfoDbData_1.2.4        HDF5Array_1.18.1             
[181] haven_2.4.3                   reshape2_1.4.4                gtable_0.3.0                 
[184] spatstat.core_2.3-2  
scRNAseq SingleCellExperiment SingleR R • 249 views
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Entering edit mode

It appears the problem is caused by the fact that there is no WuKidney.data$label.main info in the dataset.

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