Errors

[JLiLab]

Hi,

Thank you for sharing the wonderful method. Recently, I ran into issues with my new Apple silicon computer when I use cosg with a Seurat object. I could not figure out what was the problem. I will appreciate it if you can help.

marker_cosg <- COSG::cosg(seu, groups='all', assay='RNA', slot='data', mu=1, n_genes_user=2) \

Error in tabulate(genexcell[, idx_i]@i + 1) :
trying to get slot "i" from an object of a basic class ("matrix") with no slots

Here is my sessionInfo:

R version 4.2.2 (2022-10-31)
Platform: aarch64-apple-darwin20 (64-bit)
Running under: macOS Ventura 13.1

Matrix products: default
LAPACK: /Library/Frameworks/R.framework/Versions/4.2-arm64/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] stats graphics grDevices utils datasets methods base

other attached packages:
[1] forcats_0.5.2 stringr_1.5.0 dplyr_1.0.10 purrr_1.0.1 readr_2.1.3
[6] tidyr_1.2.1 tibble_3.1.8 ggplot2_3.4.0 tidyverse_1.3.2 SeuratObject_4.1.3
[11] Seurat_4.3.0

loaded via a namespace (and not attached):
[1] googledrive_2.0.0 Rtsne_0.16 colorspace_2.0-3 deldir_1.0-6
[5] ellipsis_0.3.2 ggridges_0.5.4 fs_1.5.2 rstudioapi_0.14
[9] spatstat.data_3.0-0 leiden_0.4.3 listenv_0.9.0 ggrepel_0.9.2
[13] lubridate_1.9.0 fansi_1.0.3 xml2_1.3.3 codetools_0.2-18
[17] splines_4.2.2 polyclip_1.10-4 jsonlite_1.8.4 COSG_0.9.0
[21] broom_1.0.2 ica_1.0-3 cluster_2.1.4 dbplyr_2.3.0
[25] png_0.1-8 uwot_0.1.14 shiny_1.7.4 sctransform_0.3.5
[29] spatstat.sparse_3.0-0 compiler_4.2.2 httr_1.4.4 backports_1.4.1
[33] assertthat_0.2.1 Matrix_1.5-3 fastmap_1.1.0 lazyeval_0.2.2
[37] gargle_1.2.1 cli_3.6.0 later_1.3.0 htmltools_0.5.4
[41] tools_4.2.2 igraph_1.3.5 gtable_0.3.1 glue_1.6.2
[45] RANN_2.6.1 reshape2_1.4.4 Rcpp_1.0.9 scattermore_0.8
[49] cellranger_1.1.0 vctrs_0.5.1 spatstat.explore_3.0-5 nlme_3.1-160
[53] progressr_0.13.0 lmtest_0.9-40 spatstat.random_3.0-1 globals_0.16.2
[57] rvest_1.0.3 timechange_0.2.0 mime_0.12 miniUI_0.1.1.1
[61] lifecycle_1.0.3 irlba_2.3.5.1 googlesheets4_1.0.1 goftest_1.2-3
[65] future_1.30.0 MASS_7.3-58.1 zoo_1.8-11 scales_1.2.1
[69] hms_1.1.2 promises_1.2.0.1 spatstat.utils_3.0-1 parallel_4.2.2
[73] RColorBrewer_1.1-3 reticulate_1.27 pbapply_1.7-0 gridExtra_2.3
[77] stringi_1.7.12 rlang_1.0.6 pkgconfig_2.0.3 matrixStats_0.63.0
[81] lattice_0.20-45 ROCR_1.0-11 tensor_1.5 patchwork_1.1.2
[85] htmlwidgets_1.6.1 cowplot_1.1.1 tidyselect_1.2.0 parallelly_1.34.0
[89] RcppAnnoy_0.0.20 plyr_1.8.8 magrittr_2.0.3 R6_2.5.1
[93] generics_0.1.3 DBI_1.1.3 withr_2.5.0 haven_2.5.1
[97] pillar_1.8.1 proxyC_0.3.3 fitdistrplus_1.1-8 survival_3.4-0
[101] abind_1.4-5 sp_1.5-1 future.apply_1.10.0 crayon_1.5.2
[105] modelr_0.1.10 KernSmooth_2.23-20 utf8_1.2.2 spatstat.geom_3.0-3
[109] plotly_4.10.1 tzdb_0.3.0 readxl_1.4.1 grid_4.2.2
[113] data.table_1.14.6 reprex_2.0.2 digest_0.6.31 xtable_1.8-4
[117] httpuv_1.6.8 RcppParallel_5.1.6 munsell_0.5.0 viridisLite_0.4.1

[genecell]

Hi,

Thank you for your interest! Sorry, I just saw your message, could you please try this example data (https://drive.google.com/file/d/1z-aqz08fCUJ9WmJBIPX0RIkLyEFXvirO/view?usp=share_link) and check whether the error still exists? You could also try seo@assays$RNA@data[1:4,1:4] to check the matrix is correct or not.
Thank you!

Best regards,
Min

[ventson]

Dear Min,

Great work! Really fast!
I met the sample problem when dealing with a seurat object. I think the error is caused by the extremely low number of cells in a specific celltype. When I removed the celltype that had only 1 cell, it worked! Besides, I think calculate markers for a celltype with small population (less than 10 cells or more) may be not reliable, so I filtered these celltypes before running cosg.

---

Idents(sample) <- as.character(sample$celltype)
groups_selected <- names(table(sample$celltype)[table(sample$celltype) >= 10])
marker_cosg <- cosg(sample, groups = groups_selected, assay = 'RNA', slot = 'data', mu = 10, remove_lowly_expressed = T, expressed_pct = 0.1)

Yours,
Cong

[genecell]

Dear Min,

Great work! Really fast! I met the sample problem when dealing with a seurat object. I think the error is caused by the extremely low number of cells in a specific celltype. When I removed the celltype that had only 1 cell, it worked! Besides, I think calculate markers for a celltype with small population (less than 10 cells or more) may be not reliable, so I filtered these celltypes before running cosg.

Idents(sample) <- as.character(sample$celltype)

groups_selected <- names(table(sample$celltype)[table(sample$celltype) >= 10])
marker_cosg <- cosg(sample, groups = groups_selected, assay = 'RNA', slot = 'data', mu = 10, remove_lowly_expressed = T, expressed_pct = 0.1)
Yours, Cong

Dear Cong,

Thank you for your kind words and providing the solution!
I agree with you that we need to be cautious when identifying marker genes for clusters with limited number of cells.

Best,
Min