Signac or SignacFast hang

[gianfilippo]

Hi,

I tried to test both Signac or SignacFast on the pbmc test data, following line by line the example, but after well over 10 mins, it is still showing.

I

labels = SignacFast(E = pbmc)
.......... Entry in SignacFast
.......... Running SignacFast on Seurat object :
nrow = 14043
ncol = 1222
| | 0%, ETA NA

I tried to debug it and it looks like it gets stuck within the pbmcapply function. I edited your function and replaced pbmcapply with the standard mcapply, and it completed.
I then reinstalled pbmcapply and also tried the dev version, but it does not help.

Thanks

sessionInfo()
R version 4.3.0 (2023-04-21)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Red Hat Enterprise Linux 8.6 (Ootpa)

Matrix products: default
BLAS/LAPACK: FlexiBLAS OPENBLAS; LAPACK version 3.10.1

locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] 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
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

time zone: America/New_York
tzcode source: system (glibc)

attached base packages:
[1] parallel stats4 grid stats graphics grDevices utils
[8] datasets methods base

other attached packages:
[1] SignacX_2.2.5 dsb_1.0.3
[3] SoupX_1.6.2 nat.utils_0.6.1
[5] clustree_0.5.0 ggraph_2.1.0
[7] HGNChelper_0.8.1 ProjecTILs_3.1.3
[9] DoubletFinder_2.0.3 scDblFinder_1.14.0
[11] djvdj_0.1.0 scater_1.28.0
[13] scuttle_1.10.2 SingleCellExperiment_1.22.0
[15] SummarizedExperiment_1.30.2 Biobase_2.60.0
[17] GenomicRanges_1.52.0 GenomeInfoDb_1.36.1
[19] IRanges_2.34.1 S4Vectors_0.38.1
[21] BiocGenerics_0.46.0 MatrixGenerics_1.12.2
[23] matrixStats_1.0.0 muscat_1.14.0
[25] CIPR_0.1.0 ComplexHeatmap_2.16.0
[27] gprofiler2_0.2.2 ggplot2_3.4.2
[29] cowplot_1.1.1 future_1.32.0
[31] purrr_1.0.1 openxlsx_4.2.5.2
[33] patchwork_1.1.2 miQC_1.8.0
[35] SeuratWrappers_0.3.1 SeuratDisk_0.0.0.9020
[37] glmGamPoi_1.12.2 SeuratObject_4.1.3
[39] Seurat_4.3.0.1 dplyr_1.1.2

loaded via a namespace (and not attached):
[1] R.methodsS3_1.8.2 progress_1.2.2
[3] nnet_7.3-18 goftest_1.2-3
[5] Biostrings_2.68.1 TH.data_1.1-2
[7] vctrs_0.6.2 spatstat.random_3.1-5
[9] digest_0.6.31 png_0.1-8
[11] shape_1.4.6 ggrepel_0.9.3
[13] deldir_1.0-6 parallelly_1.35.0
[15] MASS_7.3-59 reshape2_1.4.4
[17] httpuv_1.6.9 foreach_1.5.2
[19] withr_2.5.0 ellipsis_0.3.2
[21] survival_3.5-5 ggbeeswarm_0.7.2
[23] emmeans_1.8.5 zoo_1.8-12
[25] GlobalOptions_0.1.2 gtools_3.9.4
[27] pbapply_1.7-0 R.oo_1.25.0
[29] prettyunits_1.1.1 promises_1.2.0.1
[31] httr_1.4.5 restfulr_0.0.15
[33] globals_0.16.2 fitdistrplus_1.1-11
[35] miniUI_0.1.1.1 generics_0.1.3
[37] zlibbioc_1.46.0 ScaledMatrix_1.8.1
[39] polyclip_1.10-4 GenomeInfoDbData_1.2.10
[41] xtable_1.8-4 stringr_1.5.0
[43] pracma_2.4.2 doParallel_1.0.17
[45] S4Arrays_1.0.5 hms_1.1.3
[47] irlba_2.3.5.1 colorspace_2.1-0
[49] hdf5r_1.3.8 ROCR_1.0-11
[51] reticulate_1.31 spatstat.data_3.0-1
[53] flexmix_2.3-19 magrittr_2.0.3
[55] lmtest_0.9-40 readr_2.1.4
[57] later_1.3.0 viridis_0.6.2
[59] modeltools_0.2-23 lattice_0.21-8
[61] spatstat.geom_3.2-4 future.apply_1.11.0
[63] scattermore_1.2 XML_3.99-0.14
[65] RcppAnnoy_0.0.21 pillar_1.9.0
[67] nlme_3.1-162 iterators_1.0.14
[69] caTools_1.18.2 compiler_4.3.0
[71] beachmat_2.16.0 stringi_1.7.12
[73] tensor_1.5 minqa_1.2.5
[75] GenomicAlignments_1.36.0 plyr_1.8.8
[77] crayon_1.5.2 abind_1.4-5
[79] BiocIO_1.10.0 blme_1.0-5
[81] locfit_1.5-9.7 sp_2.0-0
[83] graphlayouts_1.0.0 bit_4.0.5
[85] sandwich_3.0-2 scGate_1.4.1
[87] codetools_0.2-19 multcomp_1.4-23
[89] BiocSingular_1.16.0 GetoptLong_1.0.5
[91] plotly_4.10.1 remaCor_0.0.16
[93] mime_0.12 splines_4.3.0
[95] circlize_0.4.15 Rcpp_1.0.10
[97] sparseMatrixStats_1.12.2 utf8_1.2.3
[99] clue_0.3-64 lme4_1.1-33
[101] listenv_0.9.0 DelayedMatrixStats_1.22.5
[103] Rdpack_2.4 estimability_1.4.1
[105] tibble_3.2.1 Matrix_1.5-4
[107] statmod_1.5.0 tzdb_0.3.0
[109] tweenr_2.0.2 pkgconfig_2.0.3
[111] pheatmap_1.0.12 tools_4.3.0
[113] RhpcBLASctl_0.23-42 rbibutils_2.2.13
[115] viridisLite_0.4.1 numDeriv_2016.8-1.1
[117] fastmap_1.1.1 scales_1.2.1
[119] ica_1.0-3 Rsamtools_2.16.0
[121] broom_1.0.4 abdiv_0.2.0
[123] coda_0.19-4 BiocManager_1.30.21.1
[125] RANN_2.6.1 farver_2.1.1
[127] aod_1.3.2 tidygraph_1.2.3
[129] yaml_2.3.7 rtracklayer_1.60.0
[131] cli_3.6.1 UCell_2.4.0
[133] leiden_0.4.3 lifecycle_1.0.3
[135] uwot_0.1.16 glmmTMB_1.1.7
[137] mvtnorm_1.1-3 bluster_1.10.0
[139] backports_1.4.1 BiocParallel_1.34.2
[141] gtable_0.3.3 rjson_0.2.21
[143] ggridges_0.5.4 progressr_0.13.0
[145] limma_3.56.2 jsonlite_1.8.4
[147] edgeR_3.42.4 bitops_1.0-7
[149] bit64_4.0.5 xgboost_1.7.5.1
[151] Rtsne_0.16 spatstat.utils_3.0-3
[153] BiocNeighbors_1.18.0 zip_2.3.0
[155] metapod_1.8.0 dqrng_0.3.0
[157] ggtrace_0.2.0 R.utils_2.12.2
[159] pbkrtest_0.5.2 lazyeval_0.2.2
[161] shiny_1.7.4 htmltools_0.5.5
[163] sctransform_0.3.5 glue_1.6.2
[165] XVector_0.40.0 RCurl_1.98-1.12
[167] mclust_6.0.0 scran_1.28.2
[169] gridExtra_2.3 EnvStats_2.7.0
[171] boot_1.3-28.1 igraph_1.5.1
[173] variancePartition_1.30.2 TMB_1.9.4
[175] R6_2.5.1 tidyr_1.3.0
[177] DESeq2_1.40.2 gplots_3.1.3
[179] STACAS_2.1.3 cluster_2.1.4
[181] neuralnet_1.44.2 nloptr_2.0.3
[183] DelayedArray_0.26.6 tidyselect_1.2.0
[185] vipor_0.4.5 ggforce_0.4.1
[187] rsvd_1.0.5 munsell_0.5.0
[189] KernSmooth_2.23-20 data.table_1.14.8
[191] htmlwidgets_1.6.2 RColorBrewer_1.1-3
[193] rlang_1.1.1 spatstat.sparse_3.0-2
[195] spatstat.explore_3.2-1 lmerTest_3.1-3
[197] remotes_2.4.2 fansi_1.0.4
[199] beeswarm_0.4.0

[gianfilippo]

Hi,

I should add that setting num.cores=2 and 4, even using mclapply has the same effect, i.e. it hangs

I am running the code on an interactive session on my server, with 4 cpus.

Best