The sample data of the `test_gene_enrichment()` function reports an error and cannot be used.

[zhangkaicr]

I am very grateful to the author for introducing the transcriptome analysis process based on the tidyverse system. I am currently learning the usage of the tidybulk package, but found the following errors in this function. Additionally, since the entire tidyomics system currently has a very large number of packages and their dependent environments, could your team package the entire environment into Docker to facilitate everyone's deployment? Thank you!

R version 4.4.1 (2024-06-14 ucrt) Platform: x86_64-w64-mingw32/x64 Running under: Windows 10 x64 (build 19045)

Matrix products: default

locale: [1] LC_COLLATE=Chinese (Simplified)_China.utf8 [2] LC_CTYPE=Chinese (Simplified)_China.utf8
[3] LC_MONETARY=Chinese (Simplified)_China.utf8 [4] LC_NUMERIC=C
[5] LC_TIME=Chinese (Simplified)_China.utf8

time zone: Asia/Shanghai tzcode source: internal

attached base packages: [1] stats4 stats graphics grDevices utils datasets [7] methods base

other attached packages: [1] EGSEA_1.32.0 pathview_1.44.0
[3] topGO_2.56.0 SparseM_1.83
[5] GO.db_3.19.1 graph_1.82.0
[7] AnnotationDbi_1.66.0 gage_2.54.0
[9] ggplot2_3.5.1 tidyr_1.3.1
[11] dplyr_1.1.4 tidySummarizedExperiment_1.14.0 [13] SummarizedExperiment_1.34.0 Biobase_2.64.0
[15] GenomicRanges_1.56.1 GenomeInfoDb_1.40.1
[17] IRanges_2.38.0 S4Vectors_0.42.0
[19] BiocGenerics_0.50.0 MatrixGenerics_1.16.0
[21] matrixStats_1.3.0 tidybulk_1.16.0
[23] ttservice_0.4.1

loaded via a namespace (and not attached): [1] splines_4.4.1 bitops_1.0-7
[3] tibble_3.2.1 preprocessCore_1.66.0
[5] XML_3.99-0.17 globaltest_5.58.0
[7] lifecycle_1.0.4 rstatix_0.7.2
[9] Rdpack_2.6 edgeR_4.2.0
[11] lattice_0.22-6 MASS_7.3-61
[13] hgu133plus2.db_3.13.0 backports_1.5.0
[15] magrittr_2.0.3 limma_3.60.3
[17] plotly_4.10.4 plotrix_3.8-4
[19] qqconf_1.3.2 sn_2.1.1
[21] doRNG_1.8.6 DBI_1.2.3
[23] RColorBrewer_1.1-3 HTMLUtils_0.1.9
[25] multcomp_1.4-26 abind_1.4-5
[27] zlibbioc_1.50.0 purrr_1.0.2
[29] RCurl_1.98-1.16 TH.data_1.1-2
[31] sandwich_3.1-0 GenomeInfoDbData_1.2.12
[33] KMsurv_0.1-5 irlba_2.3.5.1
[35] GSVA_1.52.3 TFisher_0.2.0
[37] annotate_1.82.0 codetools_0.2-20
[39] DelayedArray_0.30.1 DT_0.33
[41] tidyselect_1.2.1 UCSC.utils_1.0.0
[43] ScaledMatrix_1.12.0 mathjaxr_1.6-0
[45] jsonlite_1.8.8 multtest_2.60.0
[47] e1071_1.7-14 ellipsis_0.3.2
[49] survival_3.7-0 iterators_1.0.14
[51] foreach_1.5.2 tools_4.4.1
[53] Rcpp_1.0.12 glue_1.7.0
[55] gridExtra_2.3 mnormt_2.1.1
[57] SparseArray_1.4.8 xfun_0.45
[59] metap_1.11 HDF5Array_1.32.0
[61] withr_3.0.0 numDeriv_2016.8-1.1
[63] fastmap_1.2.0 rhdf5filters_1.16.0
[65] fansi_1.0.6 caTools_1.18.2
[67] digest_0.6.35 rsvd_1.0.5
[69] R6_2.5.1 colorspace_2.1-0
[71] gtools_3.9.5 RSQLite_2.3.7
[73] utf8_1.2.4 generics_0.1.3
[75] data.table_1.15.4 class_7.3-22
[77] httr_1.4.7 htmlwidgets_1.6.4
[79] S4Arrays_1.4.1 GSA_1.03.3
[81] org.Mm.eg.db_3.19.1 PADOG_1.46.0
[83] pkgconfig_2.0.3 gtable_0.3.5
[85] R2HTML_2.3.4 blob_1.2.4
[87] hwriter_1.3.2.1 SingleCellExperiment_1.26.0 [89] XVector_0.44.0 survMisc_0.5.6
[91] htmltools_0.5.8.1 carData_3.0-5
[93] GSEABase_1.66.0 org.Rn.eg.db_3.19.1
[95] scales_1.3.0 png_0.1-8
[97] SpatialExperiment_1.14.0 KEGGdzPathwaysGEO_1.42.0
[99] knitr_1.48 km.ci_0.5-6
[101] rstudioapi_0.16.0 tzdb_0.4.0
[103] rjson_0.2.21 nlme_3.1-165
[105] org.Hs.eg.db_3.19.1 proxy_0.4-27
[107] cachem_1.1.0 zoo_1.8-12
[109] rhdf5_2.48.0 safe_3.44.0
[111] stringr_1.5.1 KernSmooth_2.23-24
[113] parallel_4.4.1 hgu133a.db_3.13.0
[115] pillar_1.9.0 grid_4.4.1
[117] vctrs_0.6.5 gplots_3.1.3.1
[119] ggpubr_0.6.0 car_3.1-2
[121] BiocSingular_1.20.0 beachmat_2.20.0
[123] xtable_1.8-4 Rgraphviz_2.48.0
[125] KEGGgraph_1.64.0 readr_2.1.5
[127] magick_2.8.3 mvtnorm_1.2-5
[129] cli_3.6.3 locfit_1.5-9.10
[131] compiler_4.4.1 rlang_1.1.4
[133] crayon_1.5.3 rngtools_1.5.2
[135] ggsignif_0.6.4 mutoss_0.1-13
[137] labeling_0.4.3 survminer_0.4.9
[139] stringi_1.8.4 viridisLite_0.4.2
[141] BiocParallel_1.38.0 munsell_0.5.1
[143] Biostrings_2.72.1 lazyeval_0.2.2
[145] Matrix_1.7-0 hms_1.1.3
[147] sparseMatrixStats_1.16.0 bit64_4.0.5
[149] Rhdf5lib_1.26.0 KEGGREST_1.44.1
[151] statmod_1.5.0 rbibutils_2.2.16
[153] broom_1.0.6 memoise_2.0.1
[155] bit_4.0.5 EGSEAdata_1.32.0

[stemangiola]

Thanks. Can you please give me the entire immediate input to the code that produces an error and the exact command so I can reproduce it?

[zhangkaicr]

The code used for the test is the sample code of this function, as follows

library(SummarizedExperiment) se = tidybulk::se_mini rowData( se)$entrez = rownames(se ) df_entrez = aggregate_duplicates(se,.transcript = entrez )

library("EGSEA")

test_gene_enrichment( df_entrez, ~ condition, .sample = sample, .entrez = entrez, .abundance = count, methods = c("roast" , "safe", "gage" , "padog" , "globaltest", "ora" ), gene_sets = c("h", "c1", "c2", "c3", "c4", "c5", "c6", "c7", "kegg_disease", "kegg_metabolism", "kegg_signaling"), species="human", cores = 2 )

sessionInfo()