SCENIC
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aertslab
runSCENIC_3_scoreCells() error
Hi folks,
I am running the SCENIC pipeline. And when running runSCENIC_3_scoreCells(), I encounter the following error:
"Error in seq.int(rx[1L], rx[2L], length.out = nb) : 'from' must be a finite number"
Could someone please help regarding this? My object is fairly big. And the sessionsInfo() is as below:
R version 4.3.0 (2023-04-21) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Rocky Linux 8.7 (Green Obsidian)
Matrix products: default BLAS/LAPACK: /usr/local/intel/2022.1.2.146/mkl/2022.0.2/lib/intel64/libmkl_rt.so.2; LAPACK version 3.9.0
locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 [4] LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 [7] LC_PAPER=en_US.UTF-8 LC_NAME=C LC_ADDRESS=C [10] LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
time zone: America/New_York tzcode source: system (glibc)
attached base packages: [1] splines stats4 grid stats graphics grDevices utils datasets methods base
other attached packages: [1] doRNG_1.8.6 foreach_1.5.2 [3] gridBase_0.4-7 ComplexHeatmap_2.18.0 [5] KernSmooth_2.23-22 svglite_2.1.2 [7] GOplot_1.0.2 gridExtra_2.3 [9] ggdendro_0.1.23 DOSE_3.28.0 [11] clusterProfiler_4.10.0 MAST_1.28.0 [13] rsvd_1.0.5 TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2 [15] knitr_1.45 GGally_2.1.2 [17] EnhancedVolcano_1.20.0 reticulate_1.34.0 [19] NMF_0.26 synchronicity_1.3.5 [21] bigmemory_4.6.1 cluster_2.1.4 [23] rngtools_1.5.2 registry_0.5-1 [25] ggalluvial_0.12.5 loomR_0.2.1.9000 [27] hdf5r_1.3.8 R6_2.5.1 [29] anndata_0.7.5.6 GeneOverlap_1.38.0 [31] enrichR_3.2 BiocParallel_1.36.0 [33] Augur_1.0.3 clustree_0.5.1 [35] ggraph_2.1.0 scDblFinder_1.16.0 [37] celldex_1.12.0 scCATCH_3.2.2 [39] presto_1.0.0 gprofiler2_0.2.2 [41] scProportionTest_0.0.0.9000 phateR_1.0.7 [43] SeuratData_0.2.2 SeuratDisk_0.0.0.9020 [45] harmony_1.1.0 Rcpp_1.0.11 [47] DoubletFinder_2.0.3 RcisTarget_1.20.0 [49] AUCell_1.24.0 GENIE3_1.24.0 [51] SCENIC_1.3.1 SCopeLoomR_0.13.0 [53] scTenifoldKnk_1.0.2 synapserutils_1.0.0.15 [55] synapser_1.1.0.119 SeuratWrappers_0.3.1 [57] remotes_2.4.2.1 scTenifoldNet_1.3 [59] FactoMineR_2.9 maSigPro_1.74.0 [61] EnsDb.Hsapiens.v86_2.99.0 biomaRt_2.58.0 [63] org.Hs.eg.db_3.18.0 GSEABase_1.64.0 [65] graph_1.80.0 annotate_1.80.0 [67] XML_3.99-0.15 pathview_1.42.0 [69] enrichplot_1.22.0 GOSemSim_2.28.0 [71] annotables_0.2.0 multtest_2.58.0 [73] multcomp_1.4-25 TH.data_1.1-2 [75] MASS_7.3-60 survival_3.5-7 [77] mvtnorm_1.2-3 nlme_3.1-163 [79] future_1.33.0 qlcMatrix_0.9.7 [81] sparsesvd_0.2-2 slam_0.1-50 [83] gplots_3.1.3 gganimate_1.0.8 [85] igraph_1.5.1 rmarkdown_2.25 [87] plotly_4.10.3 kableExtra_1.3.4 [89] SingleR_2.4.0 DEGreport_1.38.0 [91] monocle_2.30.0 DDRTree_0.1.5 [93] irlba_2.3.5.1 VGAM_1.1-9 [95] monocle3_1.3.1 data.table_1.14.8 [97] RColorBrewer_1.1-3 DESeq2_1.42.0 [99] png_0.1-8 apeglm_1.24.0 [101] pheatmap_1.0.12 SingleCellExperiment_1.24.0 [103] SummarizedExperiment_1.32.0 MatrixGenerics_1.14.0 [105] matrixStats_1.1.0 reshape2_1.4.4 [107] Matrix.utils_0.9.8 ensembldb_2.26.0 [109] AnnotationFilter_1.26.0 GenomicFeatures_1.54.1 [111] AnnotationDbi_1.64.1 Biobase_2.62.0 [113] GenomicRanges_1.54.1 GenomeInfoDb_1.38.1 [115] IRanges_2.36.0 S4Vectors_0.40.1 [117] AnnotationHub_3.10.0 BiocFileCache_2.10.1 [119] dbplyr_2.4.0 BiocGenerics_0.48.1 [121] scales_1.2.1 RCurl_1.98-1.13 [123] gridGraphics_0.5-1 edgeR_4.0.1 [125] hablar_0.3.2 limma_3.58.1 [127] speckle_1.2.0 ggrepel_0.9.4 [129] Azimuth_0.4.6 shinyBS_0.61.1 [131] WGCNA_1.72-1 fastcluster_1.2.3 [133] dynamicTreeCut_1.63-1 viridis_0.6.4 [135] viridisLite_0.4.2 patchwork_1.1.3 [137] cowplot_1.1.1 Matrix_1.6-3 [139] lubridate_1.9.3 forcats_1.0.0 [141] stringr_1.5.1 dplyr_1.1.3 [143] purrr_1.0.2 readr_2.1.4 [145] tidyr_1.3.0 tibble_3.2.1 [147] ggplot2_3.4.4 tidyverse_2.0.0 [149] Seurat_5.0.0 SeuratObject_5.0.0 [151] sp_2.1-1
loaded via a namespace (and not attached): [1] httr_1.4.7 jsonlite_1.8.7 scuttle_1.12.0 [4] gtools_3.9.4 Formula_1.2-5 blob_1.2.4 [7] googlesheets4_1.1.1 RSQLite_2.3.3 pillar_1.9.0 [10] XVector_0.42.0 promises_1.2.1 polyclip_1.10-6 [13] gson_0.1.0 recipes_1.0.8 plyr_1.8.9 [16] R.oo_1.25.0 emdbook_1.3.13 tidytree_0.4.5 [19] tweenr_2.0.2 terra_1.7-55 tester_0.1.7 [22] timechange_0.2.0 usethis_2.2.2 shinyjs_2.1.0 [25] cachem_1.0.8 ROCR_1.0-11 cli_3.6.1 [28] deldir_1.0-9 memoise_2.0.1 evaluate_0.23 [31] R.methodsS3_1.8.2 parallelly_1.36.0 foreign_0.8-85 [34] tools_4.3.0 GlobalOptions_0.1.2 BiocIO_1.12.0 [37] HPO.db_0.99.2 locfit_1.5-9.8 compiler_4.3.0 [40] multcompView_0.1-9 caTools_1.18.2 ggridges_0.5.4 [43] gtable_0.3.4 fastmap_1.1.1 future.apply_1.11.0 [46] uwot_0.1.16 metapod_1.10.0 Rgraphviz_2.46.0 [49] fastDummies_1.7.3 lmtest_0.9-40 urlchecker_1.0.1 [52] BiocSingular_1.18.0 sass_0.4.7 ConsensusClusterPlus_1.66.0 [55] RhpcBLASctl_0.23-42 leiden_0.4.3 prodlim_2023.08.28 [58] shadowtext_0.1.2 dqrng_0.3.1 progress_1.2.2 [61] backports_1.4.1 lattice_0.22-5 beachmat_2.18.0 [64] checkmate_2.3.0 qvalue_2.34.0 minqa_1.2.6 [67] rvest_1.0.3 ggfun_0.1.3 colorspace_2.1-0 [70] preprocessCore_1.64.0 psych_2.3.9 WriteXLS_6.4.0 [73] timeDate_4022.108 devtools_2.4.5 GetoptLong_1.0.5 [76] zlibbioc_1.48.0 GO.db_3.18.0 tensor_1.5 [79] RSpectra_0.16-1 gower_1.0.1 lme4_1.1-35.1 [82] combinat_0.0-8 ellipsis_0.3.2 nnet_7.3-19 [85] mclust_6.0.1 mime_0.12 KEGGgraph_1.62.0 [88] fs_1.6.3 class_7.3-22 progressr_0.14.0 [91] scater_1.30.0 profvis_0.3.8 hms_1.1.3 [94] HDO.db_0.99.1 rsample_1.2.0 RcppHNSW_0.5.0 [97] SparseArray_1.2.2 DelayedArray_0.28.0 rlang_1.1.2 [100] iterators_1.0.14 yardstick_1.2.0 RcppAnnoy_0.0.21 [103] goftest_1.2-3 base64enc_0.1-3 bitops_1.0-7 [106] ExperimentHub_2.10.0 abind_1.4-5 bit_4.0.5 [109] filelock_1.0.2 clue_0.3-65 rprojroot_2.0.4 [112] Hmisc_5.1-1 ggbeeswarm_0.7.2 stringi_1.8.1 [115] scran_1.30.0 sparseMatrixStats_1.14.0 maps_3.4.1.1 [118] tidygraph_1.2.3 logging_0.10-108 here_1.0.1 [121] statmod_1.5.0 sessioninfo_1.2.2 pkgconfig_2.0.3 [124] xtable_1.8-4 spatstat.explore_3.2-5 ggplotify_0.1.2 [127] ScaledMatrix_1.10.0 Rtsne_0.16 lava_1.7.3 [130] tzdb_0.4.0 googledrive_2.1.1 KEGGREST_1.42.0 [133] docopt_0.7.1 spatstat.random_3.2-1 xgboost_1.7.5.1 [136] furrr_0.3.1 mnormt_2.1.1 doParallel_1.0.17 [139] MPO.db_0.99.7 ica_1.0-3 shinydashboard_0.7.2 [142] fitdistrplus_1.1-11 ggtree_3.10.0 Biostrings_2.70.1 [145] flashClust_1.01-2 rjson_0.2.21 bigmemory.sri_0.1.6 [148] miniUI_0.1.1.1 GenomicAlignments_1.38.0 bdsmatrix_1.3-6 [151] pals_1.8 mapproj_1.2.11 coda_0.19-4 [154] pkgload_1.3.3 bit64_4.0.5 DelayedMatrixStats_1.24.0 [157] dotCall64_1.1-0 BiocManager_1.30.22 yulab.utils_0.1.0 [160] cellranger_1.1.0 spatstat.geom_3.2-7 yaml_2.3.7 [163] impute_1.76.0 globals_0.16.2 numDeriv_2016.8-1.1 [166] bbmle_1.0.25 uuid_1.1-1 sandwich_3.0-2 [169] httpuv_1.6.12 fastICA_1.2-3 spatstat.sparse_3.0-3 [172] listenv_0.9.0 webshot_0.5.5 RANN_2.6.1 [175] htmlTable_2.4.2 admisc_0.33 generics_0.1.3 [178] ps_1.7.5 fansi_1.0.5 pkgbuild_1.4.2 [181] doMC_1.3.8 lifecycle_1.0.4 gargle_1.5.2 [184] munsell_0.5.0 callr_3.7.3 systemfonts_1.0.5 [187] rstudioapi_0.15.0 htmlwidgets_1.6.2 leaps_3.1 [190] S4Arrays_1.2.0 restfulr_0.0.15 reshape_0.8.9 [193] DBI_1.1.3 zoo_1.8-12 utf8_1.2.4 [196] treeio_1.26.0 shape_1.4.6 vctrs_0.6.4 [199] R.utils_2.12.2 bslib_0.5.1 shiny_1.7.5.1 [202] assertthat_0.2.1 interactiveDisplayBase_1.40.0 Rsamtools_2.18.0 [205] vipor_0.4.5 GenomeInfoDbData_1.2.11 BiocVersion_3.18.0 [208] ipred_0.9-14 glue_1.6.2 digest_0.6.33 [211] hardhat_1.3.0 htmltools_0.5.7 HSMMSingleCell_1.22.0 [214] broom_1.0.5 venn_1.11 processx_3.8.2 [217] later_1.3.1 ggforce_0.4.1 spatstat.utils_3.0-4 [220] emmeans_1.8.9 parsnip_1.1.1 grr_0.9.5 [223] farver_2.1.1 DT_0.30 withr_2.5.2 [226] leidenbase_0.1.25 pbapply_1.7-2 lazyeval_0.2.2 [229] magrittr_2.0.3 crayon_1.5.2 estimability_1.4.1 [232] bluster_1.12.0 xml2_1.3.5 beeswarm_0.4.0 [235] prettyunits_1.2.0 aplot_0.2.2 jquerylib_0.1.4 [238] pbmcapply_1.5.1 nloptr_2.0.3 scattermore_1.2 [241] BiocNeighbors_1.20.0 dichromat_2.0-0.1 circlize_0.4.16 [244] spam_2.10-0 rappdirs_0.3.3 arrow_13.0.0.1 [247] boot_1.3-28.
When instead of using the wrapper function [runSCENIC_3_scoreCells()], I follow the entire pipeline from the webpage (https://github.com/aertslab/SCENIC/blob/master/R/runSCENIC_3_scoreCells.R), I usually get stuck around inability to open the .openDev function for some reason. It says it couldn't find the openDev function.
Could anyone help me with this please? Thanks.
So I increased the number of cores and memory for the process and the runSCENIC_3_scoreCells() wrapper function worked fine and finished running AUCell. However, it got stuck at the plotting heatmap. It gives the following error with plotting heatmap function:
12:55 Plotting heatmap... Error in par(plt = gridPLT(), new = TRUE) : invalid value specified for graphical parameter "plt" In addition: There were 14 warnings (use warnings() to see them)
Any clues about this? Thanks.
which the ncores and ram you have used ?
So I increased the number of cores and memory for the process and the runSCENIC_3_scoreCells() wrapper function worked fine and finished running AUCell. However, it got stuck at the plotting heatmap. It gives the following error with plotting heatmap function:
12:55 Plotting heatmap... Error in par(plt = gridPLT(), new = TRUE) : invalid value specified for graphical parameter "plt" In addition: There were 14 warnings (use warnings() to see them)
Any clues about this? Thanks.
