RunVelocity() requested size is too large; suggest to enable ARMA_64BIT_WORD

[kmh005]

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   

[201931107010055zt]

Hello, I have the same problem. Have you solved it ? 😊

best Tong

[alihaotai]

no I also have such problem

[gvogler]

Same here.

[SonglingZhang]

I also encountered this problem. I had 70,000 cells, but if I randomly selected 10,000 cells, there was no such problem.