search

wguo-research / scCancer

A package for automated processing of single cell RNA-seq data in cancer
92 stars 39 forks source link

An error occur when "geneSet.method = "GSVA"" used #21

Closed dioncst closed 4 years ago

dioncst commented 4 years ago

I currently come across an error, which I'm not sure whether or not it is a bug.

My code: anno.results <- runScAnnotation( dataPath = dataPath, statPath = statPath, savePath = savePath, authorName = authorName, sampleName = sampleName, geneSet.method = "GSVA" ) The output info:

[2020-06-14 23:02:19] START: RUN scAnnotation [2020-06-14 23:02:19] -----: data preparation [2020-06-14 23:02:38] -----: Seurat object creation [2020-06-14 23:02:38] -----: highly variable genes [2020-06-14 23:02:39] -----: data scaling [2020-06-14 23:02:46] -----: PCA [2020-06-14 23:02:49] -----: clustering [2020-06-14 23:02:49] -----: tSNE [2020-06-14 23:02:57] -----: UMAP [2020-06-14 23:03:05] -----: differential expression analysis [2020-06-14 23:03:32] -----: Seurat plotting and saving When using repel, set xnudge and ynudge to 0 for optimal results [2020-06-14 23:03:41] -----: Doublet score estimation [2020-06-14 23:03:58] -----: TME cell types annotation [2020-06-14 23:04:27] -----: cells malignancy annotation

dioncst commented 4 years ago

sessionInfo() R version 3.6.3 (2020-02-29) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Ubuntu 18.04.2 LTS

Matrix products: default BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.7.1 LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.7.1

locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

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

other attached packages: [1] wesanderson_0.3.6 RColorBrewer_1.1-2 Seurat_3.1.5 scCancer_2.1.0

loaded via a namespace (and not attached): [1] readxl_1.3.1 snow_0.4-3 backports_1.1.7
[4] plyr_1.8.6 igraph_1.2.5 lazyeval_0.2.2
[7] GSEABase_1.48.0 splines_3.6.3 BiocParallel_1.20.1
[10] listenv_0.8.0 GenomeInfoDb_1.22.1 ggplot2_3.3.0
[13] digest_0.6.25 foreach_1.5.0 htmltools_0.4.0
[16] memoise_1.1.0 magrittr_1.5 cluster_2.1.0
[19] ROCR_1.0-11 limma_3.40.6 openxlsx_4.1.4
[22] globals_0.12.5 annotate_1.64.0 matrixStats_0.56.0
[25] colorspace_1.4-1 blob_1.2.1 rappdirs_0.3.1
[28] ggrepel_0.8.2 haven_2.2.0 xfun_0.13
[31] dplyr_0.8.5 crayon_1.3.4 RCurl_1.98-1.2
[34] jsonlite_1.6.1 graph_1.64.0 survival_3.1-12
[37] zoo_1.8-8 iterators_1.0.12 ape_5.3
[40] glue_1.4.0 survminer_0.4.6 gtable_0.3.0
[43] zlibbioc_1.32.0 XVector_0.26.0 leiden_0.3.3
[46] DelayedArray_0.12.3 liger_0.5.0 car_3.0-7
[49] SingleCellExperiment_1.8.0 future.apply_1.5.0 BiocGenerics_0.32.0
[52] abind_1.4-5 scales_1.1.0 pheatmap_1.0.12
[55] DBI_1.1.0 rstatix_0.5.0 miniUI_0.1.1.1
[58] Rcpp_1.0.4.6 viridisLite_0.3.0 xtable_1.8-4
[61] riverplot_0.6 reticulate_1.15 bit_1.1-15.2
[64] foreign_0.8-76 rsvd_1.0.3 mclust_5.4.6
[67] km.ci_0.5-2 NNLM_0.4.3 stats4_3.6.3
[70] tsne_0.1-3 GSVA_1.34.0 scds_1.2.0
[73] htmlwidgets_1.5.1 httr_1.4.1 FNN_1.1.3
[76] ellipsis_0.3.0 ica_1.0-2 farver_2.0.3
[79] pkgconfig_2.0.3 XML_3.99-0.3 uwot_0.1.8
[82] labeling_0.3 tidyselect_1.0.0 rlang_0.4.6
[85] reshape2_1.4.4 later_1.0.0 AnnotationDbi_1.48.0
[88] munsell_0.5.0 cellranger_1.1.0 tools_3.6.3
[91] xgboost_1.0.0.2 generics_0.0.2 RSQLite_2.2.0
[94] broom_0.5.6 ggridges_0.5.2 evaluate_0.14
[97] stringr_1.4.0 fastmap_1.0.1 npsurv_0.4-0
[100] bit64_0.9-7 knitr_1.28 fitdistrplus_1.0-14
[103] zip_2.0.4 survMisc_0.5.5 purrr_0.3.4
[106] RANN_2.6.1 pbapply_1.4-2 future_1.17.0
[109] nlme_3.1-147 mime_0.9 ggExtra_0.9
[112] shinythemes_1.1.2 compiler_3.6.3 rstudioapi_0.11
[115] plotly_4.9.2.1 curl_4.3 png_0.1-7
[118] lsei_1.2-0.1 ggsignif_0.6.0 geneplotter_1.64.0
[121] tibble_3.0.1 stringi_1.4.6 highr_0.8
[124] RSpectra_0.16-0 forcats_0.5.0 lattice_0.20-41
[127] Matrix_1.2-18 markdown_1.1 KMsurv_0.1-5
[130] vctrs_0.2.4 pillar_1.4.4 lifecycle_0.2.0
[133] lmtest_0.9-37 RcppAnnoy_0.0.16 data.table_1.12.8
[136] cowplot_1.0.0 bitops_1.0-6 irlba_2.3.3
[139] GenomicRanges_1.38.0 httpuv_1.5.2 patchwork_1.0.0
[142] R6_2.4.1 promises_1.1.0 KernSmooth_2.23-17
[145] gridExtra_2.3 rio_0.5.16 IRanges_2.20.2
[148] codetools_0.2-16 MASS_7.3-51.6 assertthat_0.2.1
[151] SummarizedExperiment_1.16.1 sctransform_0.2.1 GenomeInfoDbData_1.2.2
[154] S4Vectors_0.24.4 harmony_1.0 parallel_3.6.3
[157] doSNOW_1.0.18 hms_0.5.3 SoupX_1.2.2
[160] grid_3.6.3 tidyr_1.0.2 carData_3.0-3
[163] Rtsne_0.15 ggpubr_0.3.0 pROC_1.16.2
[166] Biobase_2.46.0 shiny_1.4.0.2

dioncst commented 4 years ago

And it's totally fine when I used (geneSet.method = "average")

wguo-research commented 4 years ago

I can run it well. Does the error still exist for the example data we provided?