Entering edit mode
7 weeks ago
Kateřina
•
0
I am trying to filter tidySummarizedExperiment object based on seqnames. I am not sure though, if I am using the filtering function correctly. Either I am missing something or it can't be used to filter rowRanges (GRanges is not accesible)? And if so, is there any tidy way to do this step? I wanna keep only standard chromosomes in my final tidySummarizedObjects. I have even tried to do it the usual way, but I was getting the warning below (and couldn't figure out, how to pipe it properly).
se_ch <- standardChromosomes(data_se)
data_se |> filter(seqnames %in% se_ch)
Error in `dplyr::filter()`:
In argument: `seqnames %in% se_ch`.
Caused by error in `match()`:
! 'match' requires vector arguments
Run `rlang::last_trace()` to see where the error occurred.
dd <- keepStandardChromosomes(data_se, pruning.mode = "coarse")
print(dd)
Warning messages:
1: Setting row names on a tibble is deprecated.
2: Setting row names on a tibble is deprecated.
3: Setting row names on a tibble is deprecated.
4: Setting row names on a tibble is deprecated.
5: Setting row names on a tibble is deprecated.
6: Setting row names on a tibble is deprecated.
7: Setting row names on a tibble is deprecated.
8: Setting row names on a tibble is deprecated.
9: Setting row names on a tibble is deprecated.
10: Setting row names on a tibble is deprecated.
11: Setting row names on a tibble is deprecated.
12: In check_se_dimnames(se) :
tidySummarizedExperiment says: the assays in your SummarizedExperiment have row names, but they don't agree with the row names of the SummarizedExperiment object itself. It is strongly recommended to make the assays consistent, to avoid erroneous matching of features.
13: Setting row names on a tibble is deprecated.
14: Setting row names on a tibble is deprecated.
sessionInfo()
R version 4.4.2 (2024-10-31)
Platform: aarch64-apple-darwin20
Running under: macOS Sequoia 15.1.1
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.0
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
time zone: Europe/Prague
tzcode source: internal
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] fission_1.26.0 lubridate_1.9.4 forcats_1.0.0
[4] stringr_1.5.1 purrr_1.0.4 readr_2.1.5
[7] tibble_3.2.1 tidyverse_2.0.0 nullranges_1.12.0
[10] plyranges_1.26.0 tidybulk_1.18.0 tidyseurat_0.8.0
[13] SeuratObject_5.0.2 sp_2.2-0 tidySingleCellExperiment_1.16.0
[16] SingleCellExperiment_1.28.1 tidySummarizedExperiment_1.16.0 ttservice_0.4.1
[19] ggplot2_3.5.1 tidyr_1.3.1 dplyr_1.1.4
[22] tidyomics_1.2.0 SummarizedExperiment_1.36.0 Biobase_2.66.0
[25] GenomicRanges_1.58.0 GenomeInfoDb_1.42.3 IRanges_2.40.1
[28] S4Vectors_0.44.0 BiocGenerics_0.52.0 MatrixGenerics_1.18.1
[31] matrixStats_1.5.0
loaded via a namespace (and not attached):
[1] RcppAnnoy_0.0.22 splines_4.4.2 later_1.4.1 BiocIO_1.16.0
[5] bitops_1.0-9 polyclip_1.10-7 preprocessCore_1.68.0 XML_3.99-0.18
[9] fastDummies_1.7.5 lifecycle_1.0.4 edgeR_4.4.2 vroom_1.6.5
[13] globals_0.16.3 lattice_0.22-6 MASS_7.3-65 magrittr_2.0.3
[17] limma_3.62.2 plotly_4.10.4 yaml_2.3.10 httpuv_1.6.15
[21] Seurat_5.2.1 sctransform_0.4.1 spam_2.11-1 spatstat.sparse_3.1-0
[25] reticulate_1.41.0 cowplot_1.1.3 pbapply_1.7-2 RColorBrewer_1.1-3
[29] abind_1.4-8 zlibbioc_1.52.0 Rtsne_0.17 RCurl_1.98-1.16
[33] GenomeInfoDbData_1.2.13 ggrepel_0.9.6 irlba_2.3.5.1 listenv_0.9.1
[37] spatstat.utils_3.1-2 goftest_1.2-3 RSpectra_0.16-2 spatstat.random_3.3-2
[41] fitdistrplus_1.2-2 parallelly_1.42.0 codetools_0.2-20 DelayedArray_0.32.0
[45] tidyselect_1.2.1 UCSC.utils_1.2.0 farver_2.1.2 spatstat.explore_3.3-4
[49] GenomicAlignments_1.42.0 jsonlite_1.9.1 ellipsis_0.3.2 progressr_0.15.1
[53] ggridges_0.5.6 survival_3.8-3 tools_4.4.2 ica_1.0-3
[57] Rcpp_1.0.14 glue_1.8.0 gridExtra_2.3 SparseArray_1.6.2
[61] withr_3.0.2 fastmap_1.2.0 fansi_1.0.6 digest_0.6.37
[65] timechange_0.3.0 R6_2.6.1 mime_0.12 colorspace_2.1-1
[69] scattermore_1.2 tensor_1.5 spatstat.data_3.1-4 utf8_1.2.4
[73] generics_0.1.3 data.table_1.17.0 rtracklayer_1.66.0 InteractionSet_1.34.0
[77] httr_1.4.7 htmlwidgets_1.6.4 S4Arrays_1.6.0 uwot_0.2.3
[81] pkgconfig_2.0.3 gtable_0.3.6 lmtest_0.9-40 XVector_0.46.0
[85] htmltools_0.5.8.1 dotCall64_1.2 scales_1.3.0 png_0.1-8
[89] spatstat.univar_3.1-1 rstudioapi_0.17.1 tzdb_0.4.0 reshape2_1.4.4
[93] rjson_0.2.23 nlme_3.1-167 curl_6.2.1 zoo_1.8-13
[97] KernSmooth_2.23-26 parallel_4.4.2 miniUI_0.1.1.1 restfulr_0.0.15
[101] pillar_1.10.1 grid_4.4.2 vctrs_0.6.5 RANN_2.6.2
[105] promises_1.3.2 xtable_1.8-4 cluster_2.1.8 locfit_1.5-9.11
[109] cli_3.6.4 compiler_4.4.2 Rsamtools_2.22.0 rlang_1.1.5
[113] crayon_1.5.3 future.apply_1.11.3 plyr_1.8.9 stringi_1.8.4
[117] viridisLite_0.4.2 deldir_2.0-4 BiocParallel_1.40.0 munsell_0.5.1
[121] Biostrings_2.74.1 lazyeval_0.2.2 spatstat.geom_3.3-5 Matrix_1.7-2
[125] RcppHNSW_0.6.0 hms_1.1.3 patchwork_1.3.0 bit64_4.6.0-1
[129] future_1.34.0 statmod_1.5.0 shiny_1.10.0 ROCR_1.0-11
[133] igraph_2.1.4 bit_4.5.0.1
Please make a reproducible example.