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vkozareva avatar vkozareva commented on August 23, 2024

Hi @davemcg, I know a reproducible example is hard in this case, but could you give us some more information about the exact line of code you ran to get this error, the exact size of your datasets, and your session info?
We've successfully used scaleNotCenter on objects of up to 900k cells on machines with less than 500G of RAM.

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davemcg avatar davemcg commented on August 23, 2024

318 mb R list of two sparse matrides

# bash
wget https://hpc.nih.gov/~mcgaugheyd/test_data.Rdata . 
# R
library(liger)
load('test_data.Rdata')
ligerex <- createLiger(test_data)
ligerex = normalize(ligerex)
ligerex = selectGenes(ligerex, var.thresh = 0.1, do.plot = FALSE)
ligerex <- scaleNotCenter(ligerex)
Error in asMethod(object) :
  Cholmod error 'problem too large' at file ../Core/cholmod_dense.c, line 105

sessionInfo()

R version 3.6.0 (2019-04-26)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

Matrix products: default
BLAS/LAPACK: /usr/local/intel/compilers_and_libraries_2019.1.144/linux/mkl/lib/intel64_lin/libmkl_rt.so

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

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base

other attached packages:
 [1] forcats_0.4.0   stringr_1.4.0   dplyr_0.8.3     purrr_0.3.2
 [5] readr_1.3.1     tidyr_0.8.3     tibble_2.1.3    tidyverse_1.2.1
 [9] liger_0.4.2     patchwork_0.0.1 Matrix_1.2-17   cowplot_0.9.4
[13] ggplot2_3.2.0

loaded via a namespace (and not attached):
 [1] tidyselect_0.2.5 ica_1.0-2        RANN.L1_2.5.2    haven_2.1.0
 [5] lattice_0.20-38  vctrs_0.2.0      colorspace_1.4-1 generics_0.0.2
 [9] doSNOW_1.0.16    snow_0.4-3       utf8_1.1.4       rlang_0.4.0
[13] pillar_1.4.2     glue_1.3.1       withr_2.1.2      readxl_1.3.1
[17] modelr_0.1.4     foreach_1.4.4    plyr_1.8.4       cellranger_1.1.0
[21] munsell_0.5.0    gtable_0.3.0     rvest_0.3.4      codetools_0.2-16
[25] riverplot_0.6    irlba_2.3.3      parallel_3.6.0   fansi_0.4.0
[29] broom_0.5.2      Rcpp_1.0.1       scales_1.0.0     backports_1.1.4
[33] jsonlite_1.6     FNN_1.1.3        hms_0.4.2        stringi_1.4.3
[37] Rtsne_0.15       ggrepel_0.8.1    grid_3.6.0       cli_1.1.0
[41] tools_3.6.0      magrittr_1.5     lazyeval_0.2.2   zeallot_0.1.0
[45] crayon_1.3.4     pkgconfig_2.0.2  xml2_1.2.0       lubridate_1.7.4
[49] rstudioapi_0.10  assertthat_0.2.1 httr_1.4.0       iterators_1.0.10
[53] R6_2.4.0         mclust_5.4.3     nlme_3.1-140     compiler_3.6.0

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davemcg avatar davemcg commented on August 23, 2024

If I split the "big" matrix into two pieces (~40k and 140k) liger runs properly

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davemcg avatar davemcg commented on August 23, 2024

scaleNotCenter works:
ligerex <- createLiger(list('A' = test_data$SRP158081[,1:150000], 'B' = test_data$SRP186407))

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