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aertslab / SCENIC

SCENIC is an R package to infer Gene Regulatory Networks and cell types from single-cell RNA-seq data.
http://scenic.aertslab.org
GNU General Public License v3.0
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runSCENIC_4_aucell_binarize error #196

Open morganee261 opened 3 years ago

morganee261 commented 3 years ago

Hello,

I am trying to run this function on my dataset runSCENIC_4_aucell_binarize and I get this error : Binary regulon activity: 26 TF regulons x 74626 cells. (26 regulons including 'extended' versions) 26 regulons are active in more than 1% (746.26) cells. Error in hclust(d, method = hclustfun) : size cannot be NA nor exceed 65536

Is that because my dataset has more than 65536 cells?

thanks for your help,

Morgane

Here is my sessionInfo() R version 4.0.5 (2021-03-31) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Ubuntu 20.04.2 LTS

Matrix products: default BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/liblapack.so.3

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] parallel grid stats graphics grDevices utils datasets methods base

other attached packages: [1] doMC_1.3.7 iterators_1.0.13 foreach_1.5.1 Biobase_2.50.0 BiocGenerics_0.36.1 SeuratObject_4.0.0
[7] Seurat_4.0.1 pheatmap_1.0.12 ggrepel_0.9.1 ggplot2_3.3.3 data.table_1.14.0 ComplexHeatmap_2.6.2 [13] BiocParallel_1.24.1 AUCell_1.12.0 SCopeLoomR_0.11.0 SCENIC_1.2.4

loaded via a namespace (and not attached): [1] utf8_1.2.1 reticulate_1.19 R.utils_2.10.1 tidyselect_1.1.0
[5] RSQLite_2.2.7 AnnotationDbi_1.52.0 htmlwidgets_1.5.3 Rtsne_0.15
[9] R2HTML_2.3.2 devtools_2.4.0 munsell_0.5.0 codetools_0.2-18
[13] ica_1.0-2 future_1.21.0 miniUI_0.1.1.1 withr_2.4.2
[17] colorspace_2.0-0 rstudioapi_0.13 stats4_4.0.5 ROCR_1.0-11
[21] tensor_1.5 listenv_0.8.0 NMF_0.23.0 MatrixGenerics_1.2.1
[25] labeling_0.4.2 GenomeInfoDbData_1.2.4 polyclip_1.10-0 bit64_4.0.5
[29] farver_2.1.0 rprojroot_2.0.2 parallelly_1.24.0 vctrs_0.3.7
[33] generics_0.1.0 R6_2.5.0 doParallel_1.0.16 GenomeInfoDb_1.26.7
[37] clue_0.3-59 hdf5r_1.3.3 bitops_1.0-7 spatstat.utils_2.1-0
[41] cachem_1.0.4 DelayedArray_0.16.3 assertthat_0.2.1 promises_1.2.0.1
[45] scales_1.1.1 gtable_0.3.0 Cairo_1.5-12.2 globals_0.14.0
[49] processx_3.5.1 goftest_1.2-2 rlang_0.4.10 GlobalOptions_0.1.2
[53] splines_4.0.5 lazyeval_0.2.2 spatstat.geom_2.1-0 yaml_2.2.1
[57] reshape2_1.4.4 abind_1.4-5 crosstalk_1.1.1 httpuv_1.6.0
[61] tools_4.0.5 usethis_2.0.1 gridBase_0.4-7 ellipsis_0.3.1
[65] spatstat.core_2.1-2 RColorBrewer_1.1-2 sessioninfo_1.1.1 ggridges_0.5.3
[69] Rcpp_1.0.6 plyr_1.8.6 zlibbioc_1.36.0 purrr_0.3.4
[73] RCurl_1.98-1.3 ps_1.6.0 prettyunits_1.1.1 rpart_4.1-15
[77] deldir_0.2-10 pbapply_1.4-3 GetoptLong_1.0.5 cowplot_1.1.1
[81] S4Vectors_0.28.1 zoo_1.8-9 SummarizedExperiment_1.20.0 cluster_2.1.2
[85] fs_1.5.0 magrittr_2.0.1 scattermore_0.7 circlize_0.4.12
[89] lmtest_0.9-38 RANN_2.6.1 fitdistrplus_1.1-3 matrixStats_0.58.0
[93] pkgload_1.2.1 patchwork_1.1.1 mime_0.10 xtable_1.8-4
[97] XML_3.99-0.6 IRanges_2.24.1 gridExtra_2.3 shape_1.4.5
[101] testthat_3.0.2 compiler_4.0.5 tibble_3.1.1 KernSmooth_2.23-18
[105] crayon_1.4.1 R.oo_1.24.0 htmltools_0.5.1.1 mgcv_1.8-35
[109] later_1.2.0 tidyr_1.1.3 DBI_1.1.1 MASS_7.3-53.1
[113] Matrix_1.3-2 cli_2.5.0 R.methodsS3_1.8.1 igraph_1.2.6
[117] GenomicRanges_1.42.0 pkgconfig_2.0.3 registry_0.5-1 plotly_4.9.3
[121] spatstat.sparse_2.0-0 annotate_1.68.0 rngtools_1.5 pkgmaker_0.32.2
[125] XVector_0.30.0 stringr_1.4.0 callr_3.7.0 digest_0.6.27
[129] sctransform_0.3.2 RcppAnnoy_0.0.18 graph_1.68.0 spatstat.data_2.1-0
[133] leiden_0.3.7 uwot_0.1.10 GSEABase_1.52.1 shiny_1.6.0
[137] rjson_0.2.20 lifecycle_1.0.0 nlme_3.1-152 jsonlite_1.7.2
[141] desc_1.3.0 viridisLite_0.4.0 fansi_0.4.2 pillar_1.6.0
[145] lattice_0.20-41 fastmap_1.1.0 httr_1.4.2 pkgbuild_1.2.0
[149] survival_3.2-11 glue_1.4.2 remotes_2.3.0 png_0.1-7
[153] bit_4.0.4 stringi_1.5.3 blob_1.2.1 memoise_2.0.0
[157] dplyr_1.0.5 irlba_2.3.3 future.apply_1.7.0

wujp1993 commented 2 years ago

hi, how did you solve the problem?

liuyifang commented 8 months ago

I meet the same error

wujp1993 commented 8 months ago

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iichelhadi commented 8 months ago

same issue. Any solution or at least explanation?

eliascrapa commented 5 months ago

Hello, I am not one of the developers but I figured out the error. In the runSCENIC_4_aucell_binarize a heatmap is called via NMF::aheatmap, which apparently does not like more than 65536 in its hierarchical clustering. To still be able to runSCENIC_4 just run: scenicOptions <- runSCENIC_4_aucell_binarize(scenicOptions, skipHeatmaps=TRUE)

wujp1993 commented 5 months ago

这是来自QQ邮箱的假期自动回复邮件。   您好，我最近正在休假中，无法亲自回复您的邮件。我将在假期结束后，尽快给您回复。

iichelhadi commented 5 months ago

Hello, I am not one of the developers but I figured out the error. In the runSCENIC_4_aucell_binarize a heatmap is called via NMF::aheatmap, which apparently does not like more than 65536 in its hierarchical clustering. To still be able to runSCENIC_4 just run: scenicOptions <- runSCENIC_4_aucell_binarize(scenicOptions, skipHeatmaps=TRUE)

Thank you @eliascrapa