junjunlab
visCluster 报错
您好，我再跑clusterGvis的函数的时候遇到报错： visCluster(object = st.data, plot.type = "heatmap", markGenes = unique(pbmc.markers1$gene), column_title_rot = 45, cluster.order = 1:9, show_column_names = F, sample.cell.order = rev(new.cluster.ids), sample.col = jjAnno::useMyCol("paired",n = 9)) 报错如下： 错误于ComplexHeatmap::Heatmap(as.matrix(mat), name = "Z-score", cluster_columns = cluster_columns, : 正式参数"show_column_names"有多个与之相对应的实际参数。 请问这是什么原因？ 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] grid splines stats4 stats graphics [6] grDevices utils datasets methods base
other attached packages:
[1] ComplexHeatmap_2.20.0 org.Hs.eg.db_3.19.1
[3] AnnotationDbi_1.66.0 IRanges_2.38.0
[5] S4Vectors_0.42.0 ClusterGVis_0.1.0
[7] monocle_2.32.0 DDRTree_0.1.5
[9] irlba_2.3.5.1 VGAM_1.1-11
[11] Biobase_2.64.0 BiocGenerics_0.50.0
[13] Matrix_1.7-0 Seurat_5.1.0
[15] lubridate_1.9.3 forcats_1.0.0
[17] stringr_1.5.1 dplyr_1.1.4
[19] purrr_1.0.2 readr_2.1.5
[21] tidyr_1.3.1 tibble_3.2.1
[23] ggplot2_3.5.1 tidyverse_2.0.0
[25] SeuratObject_5.0.2 sp_2.1-4
loaded via a namespace (and not attached):
[1] fs_1.6.4
[2] matrixStats_1.3.0
[3] spatstat.sparse_3.1-0
[4] enrichplot_1.24.0
[5] doParallel_1.0.17
[6] HDO.db_0.99.1
[7] httr_1.4.7
[8] RColorBrewer_1.1-3
[9] tools_4.4.1
[10] sctransform_0.4.1
[11] utf8_1.2.4
[12] R6_2.5.1
[13] lazyeval_0.2.2
[14] uwot_0.2.2
[15] GetoptLong_1.0.5
[16] withr_3.0.0
[17] gridExtra_2.3
[18] progressr_0.14.0
[19] cli_3.6.3
[20] Cairo_1.6-2
[21] spatstat.explore_3.2-7
[22] fastDummies_1.7.3
[23] scatterpie_0.2.3
[24] labeling_0.4.3
[25] slam_0.1-50
[26] spatstat.data_3.1-2
[27] ggridges_0.5.6
[28] pbapply_1.7-2
[29] yulab.utils_0.1.4
[30] gson_0.1.0
[31] DOSE_3.30.1
[32] parallelly_1.37.1
[33] limma_3.60.3
[34] rstudioapi_0.16.0
[35] RSQLite_2.3.7
[36] shape_1.4.6.1
[37] generics_0.1.3
[38] gridGraphics_0.5-1
[39] combinat_0.0-8
[40] ica_1.0-3
[41] spatstat.random_3.2-3
[42] GO.db_3.19.1
[43] fansi_1.0.6
[44] abind_1.4-5
[45] terra_1.7-78
[46] lifecycle_1.0.4
[47] SummarizedExperiment_1.34.0
[48] qvalue_2.36.0
[49] SparseArray_1.4.8
[50] Rtsne_0.17
[51] blob_1.2.4
[52] promises_1.3.0
[53] crayon_1.5.3
[54] miniUI_0.1.1.1
[55] lattice_0.22-6
[56] cowplot_1.1.3
[57] KEGGREST_1.44.1
[58] magick_2.8.3
[59] pillar_1.9.0
[60] fgsea_1.30.0
[61] GenomicRanges_1.56.1
[62] rjson_0.2.21
[63] boot_1.3-30
[64] future.apply_1.11.2
[65] codetools_0.2-20
[66] fastmatch_1.1-4
[67] leiden_0.4.3.1
[68] glue_1.7.0
[69] leidenbase_0.1.27
[70] ggfun_0.1.5
[71] data.table_1.15.4
[72] vctrs_0.6.5
[73] png_0.1-8
[74] treeio_1.28.0
[75] spam_2.10-0
[76] org.Mm.eg.db_3.19.1
[77] gtable_0.3.5
[78] cachem_1.1.0
[79] S4Arrays_1.4.1
[80] mime_0.12
[81] tidygraph_1.3.1
[82] HSMMSingleCell_1.24.0
[83] survival_3.7-0
[84] SingleCellExperiment_1.26.0
[85] pheatmap_1.0.12
[86] iterators_1.0.14
[87] fastICA_1.2-4
[88] statmod_1.5.0
[89] fitdistrplus_1.1-11
[90] ROCR_1.0-11
[91] nlme_3.1-165
[92] ggtree_3.12.0
[93] bit64_4.0.5
[94] RcppAnnoy_0.0.22
[95] GenomeInfoDb_1.40.1
[96] KernSmooth_2.23-24
[97] colorspace_2.1-0
[98] DBI_1.2.3
[99] tidyselect_1.2.1
[100] bit_4.0.5
[101] compiler_4.4.1
[102] DelayedArray_0.30.1
[103] plotly_4.10.4
[104] shadowtext_0.1.3
[105] scales_1.3.0
[106] lmtest_0.9-40
[107] digest_0.6.36
[108] goftest_1.2-3
[109] spatstat.utils_3.0-5
[110] presto_1.0.0
[111] minqa_1.2.7
[112] XVector_0.44.0
[113] htmltools_0.5.8.1
[114] pkgconfig_2.0.3
[115] lme4_1.1-35.5
[116] MatrixGenerics_1.16.0
[117] fastmap_1.2.0
[118] GlobalOptions_0.1.2
[119] rlang_1.1.4
[120] htmlwidgets_1.6.4
[121] UCSC.utils_1.0.0
[122] shiny_1.8.1.1
[123] farver_2.1.2
[124] zoo_1.8-12
[125] jsonlite_1.8.8
[126] BiocParallel_1.38.0
[127] GOSemSim_2.30.0
[128] magrittr_2.0.3
[129] GenomeInfoDbData_1.2.12
[130] ggplotify_0.1.2
[131] dotCall64_1.1-1
[132] patchwork_1.2.0
[133] munsell_0.5.1
[134] Rcpp_1.0.12
[135] ape_5.8
[136] viridis_0.6.5
[137] reticulate_1.38.0
[138] stringi_1.8.4
[139] ggraph_2.2.1
[140] jjAnno_0.0.3
[141] zlibbioc_1.50.0
[142] MASS_7.3-61
[143] plyr_1.8.9
[144] parallel_4.4.1
[145] listenv_0.9.1
[146] ggrepel_0.9.5
[147] deldir_2.0-4
[148] Biostrings_2.72.1
[149] graphlayouts_1.1.1
[150] tensor_1.5
[151] circlize_0.4.16
[152] hms_1.1.3
[153] igraph_2.0.3
[154] spatstat.geom_3.2-9
[155] RcppHNSW_0.6.0
[156] pkgload_1.4.0
[157] reshape2_1.4.4
[158] foreach_1.5.2
[159] nloptr_2.1.1
[160] tzdb_0.4.0
[161] tweenr_2.0.3
[162] httpuv_1.6.15
[163] RANN_2.6.1
[164] polyclip_1.10-6
[165] clue_0.3-65
[166] future_1.33.2
[167] scattermore_1.2
[168] ggforce_0.4.2
[169] xtable_1.8-4
[170] monocle3_1.3.1
[171] RSpectra_0.16-1
[172] tidytree_0.4.6
[173] later_1.3.2
[174] viridisLite_0.4.2
[175] clusterProfiler_4.12.0
[176] aplot_0.2.3
[177] memoise_2.0.1
[178] cluster_2.1.6
[179] timechange_0.3.0
[180] globals_0.16.3
