Error in getCirclize with pre-existing colname "ident" in metadata

[noigek]

Hi @ncborcherding,

thanks a lot for developing this nice collection of tools to analyze scTCR data! I came across an issue with getCirclize() recently, that might be of interest to you for future adjustments. When there is a pre-existing column "ident" in the metadata of an object, getCirclize() throws the following error: Error in group_by(): Can't transform a data frame with duplicate names. This can occur when e.g. running getCirclize() multiple times on the same object or when converting a seurat object to sce and back.

I think .grabMeta causes this error as it creates a new colum "ident" when fetching the metadata. Please find a reproducible example below. My work-around was to simply remove the pre-existing column "ident", but maybe a different colname in .grabMeta could prevent such issues in the future.

Thanks and all the best!

library(Seurat)
library(scRepertoire)

combined <- combineTCR(contig_list, samples = c("P17B", "P17L", "P18B", "P18L", 
                                    "P19B","P19L", "P20B", "P20L"))

scRep_example <- get(data("scRep_example"))
scRep_example <- combineExpression(combined, 
                                   scRep_example)

table(colnames([email protected]) %in% c("ident"))
circles <- getCirclize(scRep_example, 
                       group.by = "seurat_clusters") #works fine

################################################################

combined <- combineTCR(contig_list, samples = c("P17B", "P17L", "P18B", "P18L", 
                                    "P19B","P19L", "P20B", "P20L"))

scRep_example <- get(data("scRep_example"))
scRep_example <- combineExpression(combined, 
                                   scRep_example)
scRep_example <- as.SingleCellExperiment(scRep_example)
scRep_example <- as.Seurat(scRep_example)

table(colnames([email protected]) %in% c("ident"))
circles <- getCirclize(scRep_example,  
                       group.by = "seurat_clusters") # error in group_by()

sessionInfo()
R version 4.4.1 (2024-06-14 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 22631)

Matrix products: default

locale:
[1] LC_COLLATE=German_Germany.utf8 LC_CTYPE=German_Germany.utf8 LC_MONETARY=German_Germany.utf8
[4] LC_NUMERIC=C LC_TIME=German_Germany.utf8

time zone: Europe/Berlin
tzcode source: internal

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

other attached packages:
[1] scRepertoire_2.2.1 ggplot2_3.5.1 Seurat_5.1.0 SeuratObject_5.0.2 sp_2.1-4

loaded via a namespace (and not attached):
[1] cubature_2.1.1 RcppAnnoy_0.0.22 splines_4.4.1
[4] later_1.3.2 tibble_3.2.1 polyclip_1.10-7
[7] fastDummies_1.7.4 lifecycle_1.0.4 globals_0.16.3
[10] lattice_0.22-6 MASS_7.3-61 magrittr_2.0.3
[13] sass_0.4.9 rmarkdown_2.28 plotly_4.10.4
[16] jquerylib_0.1.4 yaml_2.3.10 httpuv_1.6.15
[19] sctransform_0.4.1 spam_2.11-0 spatstat.sparse_3.1-0
[22] reticulate_1.39.0 cowplot_1.1.3 pbapply_1.7-2
[25] RColorBrewer_1.1-3 abind_1.4-8 zlibbioc_1.50.0
[28] Rtsne_0.17 GenomicRanges_1.56.2 purrr_1.0.2
[31] ggraph_2.2.1 BiocGenerics_0.50.0 hash_2.2.6.3
[34] tweenr_2.0.3 evmix_2.12 GenomeInfoDbData_1.2.12
[37] IRanges_2.38.1 S4Vectors_0.42.1 ggrepel_0.9.6
[40] irlba_2.3.5.1 listenv_0.9.1 spatstat.utils_3.1-0
[43] iNEXT_3.0.1 MatrixModels_0.5-3 goftest_1.2-3
[46] RSpectra_0.16-2 spatstat.random_3.3-2 fitdistrplus_1.2-1
[49] parallelly_1.38.0 leiden_0.4.3.1 codetools_0.2-20
[52] DelayedArray_0.30.1 ggforce_0.4.2 tidyselect_1.2.1
[55] UCSC.utils_1.0.0 farver_2.1.2 viridis_0.6.5
[58] matrixStats_1.4.1 stats4_4.4.1 spatstat.explore_3.3-2
[61] jsonlite_1.8.9 tidygraph_1.3.1 progressr_0.14.0
[64] ggridges_0.5.6 ggalluvial_0.12.5 survival_3.7-0
[67] tools_4.4.1 stringdist_0.9.12 ica_1.0-3
[70] Rcpp_1.0.13 glue_1.8.0 gridExtra_2.3
[73] SparseArray_1.4.8 xfun_0.48 MatrixGenerics_1.16.0
[76] GenomeInfoDb_1.40.1 dplyr_1.1.4 withr_3.0.1
[79] fastmap_1.2.0 fansi_1.0.6 SparseM_1.84-2
[82] digest_0.6.37 R6_2.5.1 mime_0.12
[85] colorspace_2.1-1 scattermore_1.2 tensor_1.5
[88] spatstat.data_3.1-2 utf8_1.2.4 tidyr_1.3.1
[91] generics_0.1.3 data.table_1.16.2 graphlayouts_1.2.0
[94] httr_1.4.7 htmlwidgets_1.6.4 S4Arrays_1.4.1
[97] uwot_0.2.2 pkgconfig_2.0.3 gtable_0.3.5
[100] lmtest_0.9-40 SingleCellExperiment_1.26.0 XVector_0.44.0
[103] htmltools_0.5.8.1 dotCall64_1.2 scales_1.3.0
[106] Biobase_2.64.0 png_0.1-8 spatstat.univar_3.0-1
[109] ggdendro_0.2.0 knitr_1.48 rstudioapi_0.17.0
[112] reshape2_1.4.4 rjson_0.2.23 nlme_3.1-166
[115] zoo_1.8-12 cachem_1.1.0 stringr_1.5.1
[118] KernSmooth_2.23-24 parallel_4.4.1 miniUI_0.1.1.1
[121] pillar_1.9.0 grid_4.4.1 vctrs_0.6.5
[124] RANN_2.6.2 VGAM_1.1-12 promises_1.3.0
[127] xtable_1.8-4 cluster_2.1.6 evaluate_1.0.1
[130] truncdist_1.0-2 cli_3.6.3 compiler_4.4.1
[133] rlang_1.1.4 crayon_1.5.3 future.apply_1.11.2
[136] plyr_1.8.9 stringi_1.8.4 viridisLite_0.4.2
[139] deldir_2.0-4 assertthat_0.2.1 munsell_0.5.1
[142] gsl_2.1-8 lazyeval_0.2.2 spatstat.geom_3.3-3
[145] quantreg_5.98 Matrix_1.7-0 RcppHNSW_0.6.0
[148] patchwork_1.3.0 future_1.34.0 shiny_1.9.1
[151] SummarizedExperiment_1.34.0 evd_2.3-7.1 ROCR_1.0-11
[154] igraph_2.1.1 memoise_2.0.1 bslib_0.8.0

[ncborcherding]

Hey @noigek,

Thank you for the rundown of the issue and a great reproducible example. I am marking this as a good first issue for users because of the way you structured the issue!

The issue here is that whatever column name added will always run into a user that may have that as a preexisting column. What I have done instead is implement a message if ident column is in the meta data anytime .grabMeta().

I have added it to the dev branch and will get it more thoroughly tested before going into the main branch and biocondcutor.

Thanks again,
Nick