Create Dual Assay Seurat Object error · Issue #118 · samuel-marsh/scCustomize (original) (raw)

Hi Sam,
You really have created a wonderful resource here, thank you so much!

I am having issues with creating the dual assay Seurat object after running CellBender.
I have created two merged matrix's cell_bender and cell_ranger, but when I "CreateAssayObject" I get the following error:

Error in CreateAssayObject(counts = counts, min.cells = min.cells, min.features = min.features, :
No cell names (colnames) names present in the input matrix

Any help would be gratefully received!
Thanks
Duncan

cell_bender_merged <- Read_CellBender_h5_Multi_File(data_dir = "CB_input/", custom_name = "_e32.h5", sample_names = c("WT1", "WT2"), merge=TRUE)

cell_ranger_merged <- Read_CellBender_h5_Multi_File(data_dir = "CB_input/", custom_name = "matrix.h5", sample_names = c("WT1"), parallel = FALSE, num_cores = 1)

dual_seurat <- Create_CellBender_Merged_Seurat(raw_cell_bender_matrix = cell_bender_merged, raw_counts_matrix = cell_ranger_merged, raw_assay_name = "RAW")

sessionInfo() output

R version 4.3.1 (2023-06-16 ucrt) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows 11 x64 (build 22621)

Matrix products: default

locale: [1] LC_COLLATE=English_United Kingdom.utf8 [2] LC_CTYPE=English_United Kingdom.utf8
[3] LC_MONETARY=English_United Kingdom.utf8 [4] LC_NUMERIC=C
[5] LC_TIME=English_United Kingdom.utf8

time zone: Europe/London tzcode source: internal

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

other attached packages: [1] Matrix_1.6-0 SeuratData_0.2.1 SeuratDisk_0.0.0.9020 [4] patchwork_1.1.2 lubridate_1.9.2 forcats_1.0.0
[7] stringr_1.5.0 purrr_1.0.1 readr_2.1.4
[10] tidyr_1.3.0 tibble_3.2.1 ggplot2_3.4.2
[13] tidyverse_2.0.0 dplyr_1.1.2 qs_0.25.5
[16] scCustomize_1.1.3 SeuratObject_4.1.3 Seurat_4.3.0.1
[19] viridis_0.6.4 viridisLite_0.4.2

loaded via a namespace (and not attached): [1] RColorBrewer_1.1-3 rstudioapi_0.15.0 jsonlite_1.8.7
[4] shape_1.4.6 magrittr_2.0.3 spatstat.utils_3.0-3
[7] ggbeeswarm_0.7.2 GlobalOptions_0.1.2 vctrs_0.6.2
[10] ROCR_1.0-11 spatstat.explore_3.2-1 paletteer_1.5.0
[13] janitor_2.2.0 htmltools_0.5.5 sctransform_0.3.5
[16] parallelly_1.36.0 KernSmooth_2.23-21 htmlwidgets_1.6.2
[19] ica_1.0-3 plyr_1.8.8 plotly_4.10.2
[22] zoo_1.8-12 igraph_1.5.0.1 mime_0.12
[25] lifecycle_1.0.3 pkgconfig_2.0.3 R6_2.5.1
[28] fastmap_1.1.1 fitdistrplus_1.1-11 future_1.33.0
[31] shiny_1.7.4.1 snakecase_0.11.0 digest_0.6.33
[34] colorspace_2.1-0 rematch2_2.1.2 tensor_1.5
[37] irlba_2.3.5.1 progressr_0.13.0 fansi_1.0.4
[40] spatstat.sparse_3.0-2 timechange_0.2.0 httr_1.4.6
[43] polyclip_1.10-4 abind_1.4-5 compiler_4.3.1
[46] remotes_2.4.2.1 withr_2.5.0 bit64_4.0.5
[49] R.utils_2.12.2 MASS_7.3-60 rappdirs_0.3.3
[52] tools_4.3.1 vipor_0.4.5 lmtest_0.9-40
[55] beeswarm_0.4.0 httpuv_1.6.11 future.apply_1.11.0
[58] goftest_1.2-3 R.oo_1.25.0 glue_1.6.2
[61] nlme_3.1-162 promises_1.2.0.1 grid_4.3.1
[64] Rtsne_0.16 cluster_2.1.4 reshape2_1.4.4
[67] generics_0.1.3 hdf5r_1.3.8 gtable_0.3.3
[70] spatstat.data_3.0-1 tzdb_0.4.0 R.methodsS3_1.8.2
[73] hms_1.1.3 RApiSerialize_0.1.2 data.table_1.14.8
[76] stringfish_0.15.8 sp_2.0-0 utf8_1.2.3
[79] spatstat.geom_3.2-4 RcppAnnoy_0.0.21 ggrepel_0.9.3
[82] RANN_2.6.1 pillar_1.9.0 ggprism_1.0.4
[85] later_1.3.1 circlize_0.4.15 splines_4.3.1
[88] lattice_0.21-8 bit_4.0.5 survival_3.5-5
[91] deldir_1.0-9 tidyselect_1.2.0 miniUI_0.1.1.1
[94] pbapply_1.7-2 gridExtra_2.3 scattermore_1.2
[97] matrixStats_1.0.0 stringi_1.7.12 lazyeval_0.2.2
[100] codetools_0.2-19 BiocManager_1.30.21.1 cli_3.6.1
[103] RcppParallel_5.1.7 uwot_0.1.16 xtable_1.8-4
[106] reticulate_1.30 munsell_0.5.0 Rcpp_1.0.11
[109] globals_0.16.2 spatstat.random_3.1-5 png_0.1-8
[112] ggrastr_1.0.2 parallel_4.3.1 ellipsis_0.3.2
[115] listenv_0.9.0 scales_1.2.1 ggridges_0.5.4
[118] crayon_1.5.2 writexl_1.4.2 leiden_0.4.3
[121] rlang_1.1.0 cowplot_1.1.1