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