Closed Silve-Ruano closed 3 months ago
Hi @Silve-Ruano
Is your "st" object a Seurat v5 object? If so, bear in mind that at this moment, Beyondcell lacks support for the new layer-based structure of Seurat V5 objects and thus, you should turn on the "v4" compatibility mode.
Alternatively, you can feed your expr.matrix to bcScore directly.
Yours
No, it's a Seurat object v4 since it's the default SCT object in Beyondcell, as I'm reproducing the results from the article. I've already run the bcScore function. Thank you for your attention.
Hm, please, can you paste here your R Session information? I'm afraid beyondcell has not pinned SeuratObject correctly when installing.
R version 4.2.3 (2023-03-15 ucrt) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows 10 x64 (build 22631)
Matrix products: default
locale:
[1] LC_COLLATE=Spanish_Spain.utf8 LC_CTYPE=Spanish_Spain.utf8
[3] LC_MONETARY=Spanish_Spain.utf8 LC_NUMERIC=C
[5] LC_TIME=Spanish_Spain.utf8
attached base packages:
[1] stats graphics grDevices utils datasets methods
[7] base
other attached packages: [1] ggplot2_3.5.0 Seurat_5.0.3 SeuratObject_5.0.1 [4] sp_2.1-3 beyondcell_2.2.1
loaded via a namespace (and not attached):
[1] Rtsne_0.17 colorspace_2.1-0
[3] deldir_2.0-4 class_7.3-22
[5] ggridges_0.5.6 RcppHNSW_0.6.0
[7] rstudioapi_0.16.0 spatstat.data_3.0-4
[9] leiden_0.4.3.1 listenv_0.9.1
[11] ggrepel_0.9.5 RSpectra_0.16-1
[13] fansi_1.0.6 codetools_0.2-20
[15] splines_4.2.3 DMwR_0.4.1
[17] knitr_1.46 polyclip_1.10-6
[19] spam_2.10-0 jsonlite_1.8.8
[21] ica_1.0-3 cluster_2.1.6
[23] png_0.1-8 uwot_0.1.16
[25] shiny_1.8.1.1 sctransform_0.4.1
[27] spatstat.sparse_3.0-3 compiler_4.2.3
[29] httr_1.4.7 Matrix_1.6-5
[31] fastmap_1.1.1 lazyeval_0.2.2
[33] cli_3.6.2 later_1.3.2
[35] htmltools_0.5.8.1 tools_4.2.3
[37] igraph_2.0.3 dotCall64_1.1-1
[39] gtable_0.3.4 glue_1.7.0
[41] RANN_2.6.1 reshape2_1.4.4
[43] dplyr_1.1.4 Rcpp_1.0.12
[45] scattermore_1.2 vctrs_0.6.5
[47] nlme_3.1-164 spatstat.explore_3.2-7
[49] progressr_0.14.0 lmtest_0.9-40
[51] spatstat.random_3.2-3 xfun_0.43
[53] stringr_1.5.1 globals_0.16.3
[55] mime_0.12 miniUI_0.1.1.1
[57] lifecycle_1.0.4 irlba_2.3.5.1
[59] goftest_1.2-3 future_1.33.2
[61] MASS_7.3-60.0.1 zoo_1.8-12
[63] scales_1.3.0 promises_1.3.0
[65] spatstat.utils_3.0-4 parallel_4.2.3
[67] tidyverse_2.0.0 RColorBrewer_1.1-3
[69] curl_5.2.1 quantmod_0.4.26
[71] yaml_2.3.8 see_0.8.3
[73] reticulate_1.35.0 pbapply_1.7-2
[75] gridExtra_2.3 rpart_4.1.23
[77] stringi_1.8.3 fastDummies_1.7.3
[79] TTR_0.24.4 rlang_1.1.3
[81] pkgconfig_2.0.3 matrixStats_1.2.0
[83] evaluate_0.23 lattice_0.22-6
[85] ROCR_1.0-11 purrr_1.0.2
[87] tensor_1.5 patchwork_1.2.0
[89] htmlwidgets_1.6.4 cowplot_1.1.3
[91] tidyselect_1.2.1 parallelly_1.37.1
[93] RcppAnnoy_0.0.22 plyr_1.8.9
[95] magrittr_2.0.3 R6_2.5.1
[97] generics_0.1.3 withr_3.0.0
[99] pillar_1.9.0 xts_0.13.2
[101] fitdistrplus_1.1-11 survival_3.5-8
[103] abind_1.4-5 tibble_3.2.1
[105] future.apply_1.11.2 KernSmooth_2.23-22
[107] utf8_1.2.4 spatstat.geom_3.2-9
[109] plotly_4.10.4 rmarkdown_2.26
[111] viridis_0.6.5 grid_4.2.3
[113] data.table_1.15.4 digest_0.6.35
[115] xtable_1.8-4 tidyr_1.3.1
[117] httpuv_1.6.15 munsell_0.5.1
[119] viridisLite_0.4.2
From your SessionInfo it seems that you are indeed using seurat v5:
0 Seurat_5.0.3 SeuratObject_5.0.1
And that's causing issues because the new Seurat v5 layer structure is not currently supported by beyondcell.
Keep in mind that If your goal is to reproduce the results from the paper, you'll have to install the very first version of beyondcell too.
Thank you very much, I couldn't find the problem. I will install the first version of Beyondcell and try again.
saveRDS(sc, file = "macs2.rds") path_to_sc <- "macs2.rds" sc1 <- readRDS(path_to_sc) DefaultAssay(sc1) <- "RNA" bc <- bcScore(sc1, gs, expr.thres = 0.1) Using RNA assay as input. Error in bcScore(sc1, gs, expr.thres = 0.1) : no slot of name "counts" for this object of class "Assay5" sc1 An object of class Seurat 307908 features across 63121 samples within 1 assay Active assay: RNA (307908 features, 0 variable features) 2 layers present: counts, data
I am meeting this issue, was it also caused by the incorrect seurat version?? Thank you.
no slot of name "counts" for this object of class "Assay5"
Yes, it's very likely it's the same issue since it's looking for "counts" in an Assay5 object, which is the latest implementation of SeuratObject.
Hello! When running the![image](https://github.com/cnio-bu/beyondcell/assets/157005665/7cbb7d27-6f1b-4b0a-bd13-d2ae637cd8a5)
bcUMAP
function, I encounter an error inScaleData()
. After being prompted to runNormalizeData()
beforehand and retrying, I still encounter the error. I am using the default data (PSc, SSc, and DSS matrices). Thank you.