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cnio-bu / beyondcell

Beyondcell is a computational methodology for identifying tumour cell subpopulations with distinct drug responses in single-cell RNA-seq and Spatial Transcriptomics data.
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Error in analasys WorkFlow #158

Open jesusvaliente015 opened 5 months ago

jesusvaliente015 commented 5 months ago

Captura de pantalla 2024-04-24 192025 I am currently using seurat versiobn 4.4.0 , is this the correct version or i need a different one or is beacause another error , this is my session info

R version 4.3.0 (2023-04-21 ucrt) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows 11 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

time zone: Europe/Madrid tzcode source: internal

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

other attached packages: [1] SeuratObject_5.0.1 Seurat_4.4.0 beyondcell_2.2.1

loaded via a namespace (and not attached): [1] RColorBrewer_1.1-3 rstudioapi_0.16.0 jsonlite_1.8.8
[4] magrittr_2.0.3 spatstat.utils_3.0-4 farver_2.1.1
[7] rmarkdown_2.26 vctrs_0.6.5 ROCR_1.0-11
[10] spatstat.explore_3.2-7 htmltools_0.5.8.1 curl_5.2.1
[13] TTR_0.24.4 sctransform_0.4.1 parallelly_1.37.1
[16] KernSmooth_2.23-20 htmlwidgets_1.6.4 ica_1.0-3
[19] plyr_1.8.9 plotly_4.10.4 zoo_1.8-12
[22] igraph_2.0.3 mime_0.12 lifecycle_1.0.4
[25] pkgconfig_2.0.3 Matrix_1.6-5 R6_2.5.1
[28] fastmap_1.1.1 fitdistrplus_1.1-11 future_1.33.2
[31] shiny_1.8.1.1 digest_0.6.35 colorspace_2.1-0
[34] patchwork_1.2.0 tensor_1.5 irlba_2.3.5.1
[37] labeling_0.4.3 progressr_0.14.0 fansi_1.0.6
[40] spatstat.sparse_3.0-3 httr_1.4.7 polyclip_1.10-6
[43] abind_1.4-5 compiler_4.3.0 withr_3.0.0
[46] viridis_0.6.5 MASS_7.3-58.4 tools_4.3.0
[49] lmtest_0.9-40 quantmod_0.4.26 httpuv_1.6.15
[52] future.apply_1.11.2 goftest_1.2-3 glue_1.7.0
[55] nlme_3.1-162 promises_1.3.0 grid_4.3.0
[58] DMwR_0.4.1 Rtsne_0.17 cluster_2.1.4
[61] reshape2_1.4.4 see_0.8.3 generics_0.1.3
[64] gtable_0.3.5 spatstat.data_3.0-4 class_7.3-21
[67] tidyr_1.3.1 data.table_1.15.4 sp_2.1-3
[70] utf8_1.2.4 spatstat.geom_3.2-9 RcppAnnoy_0.0.22
[73] ggrepel_0.9.5 RANN_2.6.1 pillar_1.9.0
[76] stringr_1.5.1 spam_2.10-0 later_1.3.2
[79] splines_4.3.0 dplyr_1.1.4 lattice_0.21-8
[82] survival_3.5-5 deldir_2.0-4 tidyselect_1.2.1
[85] miniUI_0.1.1.1 pbapply_1.7-2 knitr_1.46
[88] gridExtra_2.3 scattermore_1.2 xfun_0.43
[91] matrixStats_1.3.0 stringi_1.8.3 lazyeval_0.2.2
[94] yaml_2.3.8 evaluate_0.23 codetools_0.2-19
[97] tibble_3.2.1 cli_3.6.2 uwot_0.2.1
[100] rpart_4.1.19 xtable_1.8-4 reticulate_1.36.0
[103] munsell_0.5.1 Rcpp_1.0.12 globals_0.16.3
[106] spatstat.random_3.2-3 tidyverse_2.0.0 png_0.1-8
[109] parallel_4.3.0 ggplot2_3.5.1 dotCall64_1.1-1
[112] listenv_0.9.1 viridisLite_0.4.2 scales_1.3.0
[115] xts_0.13.2 ggridges_0.5.6 leiden_0.4.3.1
[118] purrr_1.0.2 rlang_1.1.3 cowplot_1.1.3

SGMartin commented 5 months ago

Hi @jesusvaliente015

Indeed you are using the correct seurat version. Are you trying to analyze spatial transcriptomics data or a regular single cell dataset?

jesusvaliente015 commented 5 months ago

Hi @SGMartin i am using a single cell dataset

SGMartin commented 5 months ago

Hi @jesusvaliente015

Taking a look at your sessionInfo it seems that you are using Seurat v4 but SeuratObject v5:

 [1] SeuratObject_5.0.1 Seurat_4.4.0 beyondcell_2.2.1

Try to run seurat in v4 compatibility mode before running beyondcell.