seurat-wrappers
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RunVelocity() requested size is too large; suggest to enable ARMA_64BIT_WORD
Hello,
I'm having an issue with RunVelocity failing on a 480GB highmem machine (originally tried on 150GB). This seems similar to #21 . I'm not sure I can get a higher mem machine on this cluster. This object is the only one loaded in the session. Any advice would be much appreciated! Thanks!
seurat_combined3 <- RunVelocity(object = seurat_combined3, deltaT = 1, kCells = 25, fit.quantile = 0.02)
Filtering genes in the spliced matrix
Filtering genes in the unspliced matrix
Calculating embedding distance matrix
Error in arma_mat_cor(mat) :
Mat::init(): requested size is too large; suggest to enable ARMA_64BIT_WORD
dim(seurat_combined3)
[1] 19888 108455
> sessionInfo()
R version 4.1.0 (2021-05-18)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)
Matrix products: default
BLAS: /usr/lib64/libblas.so.3.4.2
LAPACK: /usr/lib64/liblapack.so.3.4.2
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
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] SeuratWrappers_0.3.0 velocyto.R_0.6 Matrix_1.3-4 SeuratObject_4.0.2
[5] Seurat_4.0.4
loaded via a namespace (and not attached):
[1] nlme_3.1-152 matrixStats_0.61.0 spatstat.sparse_2.0-0 RcppAnnoy_0.0.19
[5] RColorBrewer_1.1-2 httr_1.4.2 sctransform_0.3.2 tools_4.1.0
[9] utf8_1.2.2 R6_2.5.1 irlba_2.3.3 rpart_4.1-15
[13] KernSmooth_2.23-20 BiocGenerics_0.38.0 uwot_0.1.10 mgcv_1.8-35
[17] DBI_1.1.1 lazyeval_0.2.2 colorspace_2.0-2 tidyselect_1.1.1
[21] gridExtra_2.3 compiler_4.1.0 Biobase_2.52.0 plotly_4.9.4.1
[25] scales_1.1.1 lmtest_0.9-38 spatstat.data_2.1-0 ggridges_0.5.3
[29] pbapply_1.5-0 goftest_1.2-3 stringr_1.4.0 digest_0.6.28
[33] spatstat.utils_2.2-0 R.utils_2.11.0 pkgconfig_2.0.3 htmltools_0.5.2
[37] parallelly_1.28.1 fastmap_1.1.0 htmlwidgets_1.5.4 rlang_0.4.12
[41] shiny_1.7.1 generics_0.1.1 zoo_1.8-9 jsonlite_1.7.2
[45] ica_1.0-2 R.oo_1.24.0 dplyr_1.0.7 magrittr_2.0.1
[49] patchwork_1.1.1 Rcpp_1.0.7 munsell_0.5.0 fansi_0.5.0
[53] abind_1.4-5 reticulate_1.22 R.methodsS3_1.8.1 lifecycle_1.0.1
[57] stringi_1.7.5 MASS_7.3-54 Rtsne_0.15 plyr_1.8.6
[61] grid_4.1.0 parallel_4.1.0 listenv_0.8.0 promises_1.2.0.1
[65] ggrepel_0.9.1 crayon_1.4.1 miniUI_0.1.1.1 deldir_1.0-6
[69] lattice_0.20-44 cowplot_1.1.1 splines_4.1.0 tensor_1.5
[73] pillar_1.6.3 igraph_1.2.7 spatstat.geom_2.3-0 future.apply_1.8.1
[77] reshape2_1.4.4 codetools_0.2-18 leiden_0.3.9 glue_1.4.2
[81] remotes_2.4.0 BiocManager_1.30.16 pcaMethods_1.82.0 data.table_1.14.2
[85] png_0.1-7 vctrs_0.3.8 httpuv_1.6.3 gtable_0.3.0
[89] RANN_2.6.1 purrr_0.3.4 spatstat.core_2.3-0 polyclip_1.10-0
[93] tidyr_1.1.4 scattermore_0.7 future_1.22.1 assertthat_0.2.1
[97] ggplot2_3.3.5 rsvd_1.0.5 mime_0.12 xtable_1.8-4
[101] later_1.3.0 survival_3.2-11 viridisLite_0.4.0 tibble_3.1.5
[105] cluster_2.1.2 globals_0.14.0 fitdistrplus_1.1-6 ellipsis_0.3.2
[109] ROCR_1.0-11
Hello, I have the same problem. Have you solved it ? 😊
best Tong
no I also have such problem
Same here.
I also encountered this problem. I had 70,000 cells, but if I randomly selected 10,000 cells, there was no such problem.