Closed duocang closed 3 years ago
ChristophH
commented
3 years ago Hi,
There are only 900 genes being used to estimate the parameters - that's not a problem, but lower than the default and makes me wonder whether something with your input matrix is off. Can you share the input object, so I can have a look?
Also, always run traceback() after seeing the error and share the output as that can help to pinpoint the problem.
duocang
commented
3 years ago Hi @ChristophH
I have deleted the small data so I uploaded a bit one into OneDeive (1gb) , please feel free to try it out. https://1drv.ms/u/s!AtjLM4-mbBLkx8s9GP9060v5lrsxKQ?e=Of1bZX
I have tried the data again, still the same erro.
>seu <- readRDS(here("test_result/seurat_before_sct.rds"))
> seu <- SCTransform(seu, assay = "RNA", variable.features.n=500,
+ new.assay.name = "SCT", verbose = TRUE)
Calculating cell attributes from input UMI matrix: log_umi
Variance stabilizing transformation of count matrix of size 24718 by 17542
Model formula is y ~ log_umi
Get Negative Binomial regression parameters per gene
Using 2000 genes, 5000 cells
| | 0%Error: node stack overflow
Error during wrapup: node stack overflow
Error: no more error handlers available (recursive errors?); invoking 'abort' restart
> traceback()
No traceback available
> I cannot reproduce the error. The output I see is
Calculating cell attributes from input UMI matrix: log_umi
Variance stabilizing transformation of count matrix of size 24718 by 17542
Model formula is y ~ log_umi
Get Negative Binomial regression parameters per gene
Using 2000 genes, 5000 cells
|=====================================================================| 100%
Found 39 outliers - those will be ignored in fitting/regularization step
Second step: Get residuals using fitted parameters for 24718 genes
|=====================================================================| 100%
Computing corrected count matrix for 24718 genes
|=====================================================================| 100%I then run out of memory, but that was expected. If I pass the conserve.memory = TRUE parameter to Seurat::SCTransform it finishes without a problem.
Which versions of Seurat and sctransform are you using? You could try updating to the develop version of sctransform (remotes::install_github("ChristophH/sctransform@develop")) and Seurat (remotes::install_github("satijalab/seurat@release/4.0.0")).
In case it helps, here is my session info:
R version 4.0.2 (2020-06-22)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Catalina 10.15.7
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] Seurat_3.9.9.9008 sctransform_0.3.2.9000 Matrix_1.2-18
loaded via a namespace (and not attached):
[1] Rtsne_0.15 colorspace_2.0-0
[3] deldir_0.1-29 ellipsis_0.3.1
[5] ggridges_0.5.2 XVector_0.28.0
[7] GenomicRanges_1.40.0 spatstat.data_1.4-3
[9] leiden_0.3.3 listenv_0.8.0
[11] ggrepel_0.8.2 codetools_0.2-16
[13] splines_4.0.2 knitr_1.30
[15] polyclip_1.10-0 jsonlite_1.7.2
[17] ica_1.0-2 cluster_2.1.0
[19] png_0.1-7 uwot_0.1.8.9001
[21] shiny_1.5.0 compiler_4.0.2
[23] httr_1.4.2 fastmap_1.0.1
[25] lazyeval_0.2.2 later_1.1.0.1
[27] htmltools_0.5.0 tools_4.0.2
[29] rsvd_1.0.3 igraph_1.2.6
[31] gtable_0.3.0 glue_1.4.2
[33] GenomeInfoDbData_1.2.3 RANN_2.6.1
[35] reshape2_1.4.4 dplyr_1.0.2
[37] rappdirs_0.3.1 tinytex_0.27
[39] Rcpp_1.0.5 spatstat_1.64-1
[41] Biobase_2.48.0 vctrs_0.3.5
[43] nlme_3.1-149 lmtest_0.9-38
[45] xfun_0.19 stringr_1.4.0
[47] globals_0.13.1 mime_0.9
[49] miniUI_0.1.1.1 lifecycle_0.2.0
[51] irlba_2.3.3 goftest_1.2-2
[53] future_1.19.1 zlibbioc_1.34.0
[55] MASS_7.3-53 zoo_1.8-8
[57] scales_1.1.1 promises_1.1.1
[59] spatstat.utils_1.17-0 parallel_4.0.2
[61] SummarizedExperiment_1.18.2 RColorBrewer_1.1-2
[63] yaml_2.2.1 reticulate_1.16
[65] pbapply_1.4-3 gridExtra_2.3
[67] ggplot2_3.3.2 rpart_4.1-15
[69] stringi_1.5.3 S4Vectors_0.26.1
[71] BiocGenerics_0.34.0 GenomeInfoDb_1.24.2
[73] rlang_0.4.9 pkgconfig_2.0.3
[75] matrixStats_0.57.0 bitops_1.0-6
[77] evaluate_0.14 lattice_0.20-41
[79] glmGamPoi_1.3.4 tensor_1.5
[81] ROCR_1.0-11 purrr_0.3.4
[83] patchwork_1.1.0.9000 htmlwidgets_1.5.2
[85] cowplot_1.1.0 tidyselect_1.1.0
[87] RcppAnnoy_0.0.16 plyr_1.8.6
[89] magrittr_2.0.1 R6_2.5.0
[91] IRanges_2.22.2 generics_0.0.2
[93] DelayedArray_0.14.1 mgcv_1.8-33
[95] pillar_1.4.7 fitdistrplus_1.1-1
[97] abind_1.4-5 survival_3.2-3
[99] RCurl_1.98-1.2 tibble_3.0.4
[101] future.apply_1.6.0 crayon_1.3.4.9000
[103] KernSmooth_2.23-17 plotly_4.9.2.1
[105] rmarkdown_2.5 grid_4.0.2
[107] data.table_1.13.2 digest_0.6.27
[109] xtable_1.8-4 tidyr_1.1.2
[111] httpuv_1.5.4 stats4_4.0.2
[113] munsell_0.5.0 viridisLite_0.3.0 @ChristophH Thank you for trying.
I have realized this could be a problem of R-project configuration.
SCTransform works well when setwd to a new environment. I am not sure what is the issue but it should be clear that it is not a problem from SCTransfrom.
duocang
commented
3 years ago Just in case someone meets this problem again.
Solution: Try another version of RStudio.
After one month of coding with Seurat, I met the problem again and had no clue why it happens(no coding even chagned).
I tried an old version RStudio and the problem is gone. I am just tried of debugging into R Library any more.
Hi.
I am doing normal Seruat data process.
I tried with a very small dataset to run
SCTransofrmbut there is always an error. I got 32 GB RAM so I do not think it is a RAM problem.If I save the Seurat object locally and then read the .rds and do
SCTransformin other folder it works.I have been stuck in this place for days and there is not much information concerning this.
Thank you!
@ChristophH tried
traceback(), NO traceback available.