l-magnificence
commented
3 months ago This is because the update of GSVA, in which the previous API of GSVA has been changed to make use of parameter objects. see https://github.com/rcastelo/GSVA/issues/172 If previously you have used
gsva_es <- gsva(as.matrix(gsym.expr), gs)all you need to do is change it to
gsva_es <- gsva(gsvaParam(as.matrix(gsym.expr), gs))Now, you can use old version GSVA (such as 1.40.1) And we will update Mime later.
您好，我刚重新安装的Mime包，包括依赖的包。用自带数据进行分析，然后我运行函数 auc.other.pre <- cal_auc_previous_sig(list_train_vali_Data = list_train_vali_Data,seed = 5201314, train_data = list_train_vali_Data$training, cores_for_parallel = 32) 报错提示： 错误于gsva(expr, gmt, method = "ssgsea", parallel.sz = 1): Calling gsva(expr=., gset.idx.list=., method=., ...) is defunct; use a method-specific parameter object (see '?gsva'). 请问这是什么情况？
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=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 parallel stats graphics grDevices [6] utils datasets methods base
other attached packages: [1] GSEABase_1.66.0 graph_1.82.0
[3] annotate_1.82.0 XML_3.99-0.17
[5] AnnotationDbi_1.66.0 IRanges_2.38.0
[7] S4Vectors_0.42.0 GSVA_1.52.3
[9] sparrow_1.10.1 MASS_7.3-61
[11] dplyr_1.1.4 cancerclass_1.48.0
[13] binom_1.1-1.1 Biobase_2.64.0
[15] BiocGenerics_0.50.0 doParallel_1.0.17
[17] iterators_1.0.14 foreach_1.5.2
[19] caret_6.0-94 lattice_0.22-6
[21] ggplot2_3.5.1 ROCit_2.1.2
[23] pROC_1.18.5 e1071_1.7-14
[25] sva_3.52.0 BiocParallel_1.38.0 [27] genefilter_1.86.0 mgcv_1.9-1
[29] nlme_3.1-165 future_1.33.2
[31] gridExtra_2.3 stringr_1.5.1
[33] Mime_0.0.0.9000
loaded via a namespace (and not attached): [1] splines_4.4.1
[2] later_1.3.2
[3] BiocIO_1.14.0
[4] ggplotify_0.1.2
[5] tibble_3.2.1
[6] hardhat_1.4.0
[7] rpart_4.1.23
[8] lifecycle_1.0.4
[9] edgeR_4.2.0
[10] globals_0.16.3
[11] backports_1.5.0
[12] magrittr_2.0.3
[13] limma_3.60.3
[14] plotly_4.10.4
[15] httpuv_1.6.15
[16] DBI_1.2.3
[17] RColorBrewer_1.1-3
[18] lubridate_1.9.3
[19] abind_1.4-5
[20] zlibbioc_1.50.0
[21] GenomicRanges_1.56.1
[22] purrr_1.0.2
[23] yulab.utils_0.1.4
[24] nnet_7.3-19
[25] ipred_0.9-14
[26] circlize_0.4.16
[27] lava_1.8.0
[28] GenomeInfoDbData_1.2.12
[29] irlba_2.3.5.1
[30] listenv_0.9.1
[31] parallelly_1.37.1
[32] codetools_0.2-20
[33] DelayedArray_0.30.1
[34] tidyselect_1.2.1
[35] shape_1.4.6.1
[36] aplot_0.2.3
[37] UCSC.utils_1.0.0
[38] ScaledMatrix_1.12.0
[39] viridis_0.6.5
[40] matrixStats_1.3.0
[41] jsonlite_1.8.8
[42] GetoptLong_1.0.5
[43] survival_3.7-0
[44] tools_4.4.1
[45] Rcpp_1.0.12
[46] glue_1.7.0
[47] prodlim_2024.06.25
[48] SparseArray_1.4.8
[49] MatrixGenerics_1.16.0
[50] GenomeInfoDb_1.40.1
[51] HDF5Array_1.32.0
[52] withr_3.0.0
[53] combinat_0.0-8
[54] fastmap_1.2.0
[55] rhdf5filters_1.16.0
[56] fansi_1.0.6
[57] digest_0.6.36
[58] rsvd_1.0.5
[59] timechange_0.3.0
[60] R6_2.5.1
[61] gridGraphics_0.5-1
[62] colorspace_2.1-0
[63] RSQLite_2.3.7
[64] utf8_1.2.4
[65] tidyr_1.3.1
[66] generics_0.1.3
[67] data.table_1.15.4
[68] recipes_1.0.10
[69] class_7.3-22
[70] httr_1.4.7
[71] htmlwidgets_1.6.4
[72] S4Arrays_1.4.1
[73] ontologyIndex_2.12
[74] ModelMetrics_1.2.2.2
[75] pkgconfig_2.0.3
[76] gtable_0.3.5
[77] timeDate_4032.109
[78] blob_1.2.4
[79] ComplexHeatmap_2.20.0
[80] SingleCellExperiment_1.26.0 [81] XVector_0.44.0
[82] htmltools_0.5.8.1
[83] clue_0.3-65
[84] scales_1.3.0
[85] png_0.1-8
[86] SpatialExperiment_1.14.0
[87] gower_1.0.1
[88] ggfun_0.1.5
[89] rstudioapi_0.16.0
[90] reshape2_1.4.4
[91] rjson_0.2.21
[92] checkmate_2.3.1
[93] rhdf5_2.48.0
[94] proxy_0.4-27
[95] cachem_1.1.0
[96] GlobalOptions_0.1.2
[97] BiocSet_1.18.0
[98] pillar_1.9.0
[99] grid_4.4.1
[100] vctrs_0.6.5
[101] promises_1.3.0
[102] BiocSingular_1.20.0
[103] beachmat_2.20.0
[104] xtable_1.8-4
[105] cluster_2.1.6
[106] magick_2.8.3
[107] cli_3.6.3
[108] locfit_1.5-9.10
[109] compiler_4.4.1
[110] rlang_1.1.4
[111] crayon_1.5.3
[112] future.apply_1.11.2
[113] plyr_1.8.9
[114] fs_1.6.4
[115] stringi_1.8.4
[116] viridisLite_0.4.2
[117] babelgene_22.9
[118] munsell_0.5.1
[119] Biostrings_2.72.1
[120] lazyeval_0.2.2
[121] Matrix_1.7-0
[122] patchwork_1.2.0
[123] sparseMatrixStats_1.16.0
[124] bit64_4.0.5
[125] Rhdf5lib_1.26.0
[126] KEGGREST_1.44.1
[127] statmod_1.5.0
[128] SummarizedExperiment_1.34.0 [129] memoise_2.0.1
[130] bit_4.0.5