Error in validObject(object = object) : invalid class “Assay5” object: Layers must be two-dimensional objects #173
Description
Dear Team,
Thank you for developing and maintaining this wonderful package — it has been extremely useful in my analyses.
However, I have recently encountered the same error across multiple projects.
`
library(Seurat)
library(ggplot2)
library(ggpubr)
library(escape)
library(dplyr)
all_gobp <- getGeneSets(library = "C5", subcategory = "GO:BP")
Loading required namespace: GSEABase
View(all_gobp)
#CMS1_SERINE_TRANSPORT
GS.gobp <- all_gobp[["GOBP-ONE-CARBON-METABOLISM-PATHWAY"]]
#CMS1_SERINE_TRANSPORT
GS.gobp <- all_gobp[["GOBP-ONE-CARBON-METABOLIC-PROCESS"]]
escape_result <- runEscape(
input.data = Tcell,
gene.sets = list("GOBP-ONE-CARBON-METABOLIC-PROCESS" = GS.gobp)
)
Error inGetAssayData():
! GetAssayData doesn't work for multiple layers in v5 assay.
Runrlang::last_trace()to see where the error occurred.`
To address this, I tried converting the assay as follows:
Tcell[["RNA"]] <- as(object = Tcell[["RNA"]], Class = "Assay")
However, the same error persists.
Error in GetAssayData():
! GetAssayData doesn't work for multiple layers in v5 assay.
Run rlang::last_trace() to see where the error occurred.
I would greatly appreciate your guidance on resolving this issue. My session information is provided below for reference.
sessionInfo()
R version 4.5.1 (2025-06-13 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 26100)
Matrix products: default
LAPACK version 3.12.1
locale:
[1] LC_COLLATE=Korean_Korea.utf8 LC_CTYPE=Korean_Korea.utf8 LC_MONETARY=Korean_Korea.utf8 LC_NUMERIC=C LC_TIME=Korean_Korea.utf8
time zone: Asia/Seoul
tzcode source: internal
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] escape_2.5.5 ggpubr_0.6.2 ggplot2_4.0.0 future_1.67.0 hdf5r_1.3.12 Matrix_1.7-3 patchwork_1.3.2 Seurat_5.3.0 SeuratObject_5.1.0 sp_2.2-0
[11] dplyr_1.1.4
loaded via a namespace (and not attached):
[1] RcppAnnoy_0.0.22 splines_4.5.1 later_1.4.2 tibble_3.3.0 polyclip_1.10-7 graph_1.86.0 XML_3.99-0.18
[8] fastDummies_1.7.5 lifecycle_1.0.4 rstatix_0.7.2 globals_0.18.0 lattice_0.22-7 MASS_7.3-65 ggdist_3.3.3
[15] backports_1.5.0 magrittr_2.0.3 plotly_4.11.0 httpuv_1.6.16 sctransform_0.4.2 spam_2.11-1 spatstat.sparse_3.1-0
[22] reticulate_1.43.0 cowplot_1.2.0 pbapply_1.7-4 DBI_1.2.3 RColorBrewer_1.1-3 abind_1.4-8 Rtsne_0.17
[29] GenomicRanges_1.60.0 purrr_1.1.0 BiocGenerics_0.54.1 GenomeInfoDbData_1.2.14 IRanges_2.42.0 S4Vectors_0.46.0 ggrepel_0.9.6
[36] irlba_2.3.5.1 listenv_0.9.1 spatstat.utils_3.2-0 GSVA_2.2.1 goftest_1.2-3 RSpectra_0.16-2 spatstat.random_3.4-2
[43] annotate_1.86.1 fitdistrplus_1.2-4 parallelly_1.45.0 DelayedMatrixStats_1.30.0 codetools_0.2-20 DelayedArray_0.34.1 tidyselect_1.2.1
[50] UCSC.utils_1.4.0 farver_2.1.2 ScaledMatrix_1.16.0 matrixStats_1.5.0 stats4_4.5.1 spatstat.explore_3.5-3 jsonlite_2.0.0
[57] progressr_0.17.0 Formula_1.2-5 ggridges_0.5.7 survival_3.8-3 tools_4.5.1 ica_1.0-3 Rcpp_1.1.0
[64] glue_1.8.0 gridExtra_2.3 SparseArray_1.8.1 MatrixGenerics_1.20.0 distributional_0.5.0 GenomeInfoDb_1.44.3 HDF5Array_1.36.0
[71] withr_3.0.2 fastmap_1.2.0 rhdf5filters_1.20.0 rsvd_1.0.5 digest_0.6.37 R6_2.6.1 mime_0.13
[78] scattermore_1.2 tensor_1.5.1 dichromat_2.0-0.1 spatstat.data_3.1-9 RSQLite_2.4.3 h5mread_1.0.1 tidyr_1.3.1
[85] generics_0.1.4 data.table_1.17.8 httr_1.4.7 htmlwidgets_1.6.4 S4Arrays_1.8.1 uwot_0.2.3 pkgconfig_2.0.3
[92] gtable_0.3.6 blob_1.2.4 lmtest_0.9-40 S7_0.2.0 SingleCellExperiment_1.30.1 XVector_0.48.0 htmltools_0.5.8.1
[99] carData_3.0-5 dotCall64_1.2 GSEABase_1.70.1 scales_1.4.0 Biobase_2.68.0 png_0.1-8 SpatialExperiment_1.18.1
[106] spatstat.univar_3.1-4 rstudioapi_0.17.1 rjson_0.2.23 reshape2_1.4.4 nlme_3.1-168 rhdf5_2.52.1 zoo_1.8-14
[113] cachem_1.1.0 stringr_1.5.2 KernSmooth_2.23-26 parallel_4.5.1 miniUI_0.1.2 vipor_0.4.7 AnnotationDbi_1.70.0
[120] ggrastr_1.0.2 pillar_1.11.1 grid_4.5.1 vctrs_0.6.5 RANN_2.6.2 promises_1.3.3 BiocSingular_1.24.0
[127] car_3.1-3 beachmat_2.24.0 xtable_1.8-4 cluster_2.1.8.1 beeswarm_0.4.0 magick_2.9.0 cli_3.6.5
[134] compiler_4.5.1 rlang_1.1.6 crayon_1.5.3 future.apply_1.20.0 ggsignif_0.6.4 labeling_0.4.3 plyr_1.8.9
[141] ggbeeswarm_0.7.2 stringi_1.8.7 BiocParallel_1.42.2 viridisLite_0.4.2 deldir_2.0-4 Biostrings_2.76.0 lazyeval_0.2.2
[148] spatstat.geom_3.6-0 RcppHNSW_0.6.0 sparseMatrixStats_1.20.0 bit64_4.6.0-1 Rhdf5lib_1.30.0 KEGGREST_1.48.1 shiny_1.11.1
[155] SummarizedExperiment_1.38.1 ROCR_1.0-11 igraph_2.1.4 broom_1.0.10 memoise_2.0.1 bit_4.6.0
Thank you for your time and for your continued support of this excellent package.
Best regards,
222222spam