Error: C stack usage 10847362 is too close to the limit

[Carota-1]

I got an error of "Error: C stack usage 10847362 is too close to the limit" when I run

bsseq_stranded = read.bismark(
  files = files,
  colData = data.frame(row.names = c("WT56","WT57","WT58","MU63","MU67","WT68","WT75","MU76","MU80","WT89","MU96","MU97","WT01","WT10","MU13","WT19","MU827","WT837","WT850","WT856","WT867","MU880","MU894")),
  rmZeroCov = FALSE,
  strandCollapse = TRUE,nThread=1
)

for 23 samples.
How can I resolve it?

[PeteHaitch]

Impossible to know with that little information.

E.g.,

• Does it work if you process 1 sample?
• What version of bsseq?
• What's the output of BiocManager::valid() and sessionInfo()?
• What species and methylation context are you processing?

[Carota-1]

1.Error reporting has not gone away if I process 1 sample.
2. bsseq’ version 1.30.0
4. human,

3. BiocManager::valid()
   'getOption("repos")' replaces Bioconductor standard repositories, see '?repositories' for details

replacement repositories:
CRAN: https://mirrors.ustc.edu.cn/CRAN/

• sessionInfo()

R version 4.1.1 (2021-08-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.4 LTS

Matrix products: default
BLAS/LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.8.so

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

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

other attached packages:
[1] bsseq_1.30.0 SummarizedExperiment_1.24.0 Biobase_2.54.0 MatrixGenerics_1.6.0
[5] matrixStats_0.61.0 GenomicRanges_1.46.1 GenomeInfoDb_1.30.1 IRanges_2.28.0
[9] S4Vectors_0.32.4 BiocGenerics_0.40.0 methylSig_1.7.0 BiocManager_1.30.16

loaded via a namespace (and not attached):
[1] pkgload_1.2.4 splines_4.1.1 R.utils_2.11.0 DelayedMatrixStats_1.16.0
[5] gtools_3.9.2 brio_1.1.3 Rsamtools_2.10.0 BSgenome_1.62.0
[9] GenomeInfoDbData_1.2.7 yaml_2.3.5 remotes_2.4.2 sessioninfo_1.2.2
[13] lattice_0.20-45 glue_1.6.2 limma_3.50.1 XVector_0.34.0
[17] colorspace_2.0-3 R.oo_1.24.0 Matrix_1.4-1 XML_3.99-0.9
[21] devtools_2.4.3 DSS_2.42.0 zlibbioc_1.40.0 purrr_0.3.4
[25] scales_1.1.1 processx_3.5.3 HDF5Array_1.22.1 BiocParallel_1.28.3
[29] usethis_2.1.5 ellipsis_0.3.2 cachem_1.0.6 withr_2.5.0
[33] cli_3.2.0 magrittr_2.0.3 crayon_1.5.1 memoise_2.0.1
[37] ps_1.6.0 R.methodsS3_1.8.1 fs_1.5.2 pkgbuild_1.3.1
[41] tools_4.1.1 data.table_1.14.2 prettyunits_1.1.1 BiocIO_1.4.0
[45] lifecycle_1.0.1 Rhdf5lib_1.16.0 munsell_0.5.0 locfit_1.5-9.5
[49] DelayedArray_0.20.0 callr_3.7.0 Biostrings_2.62.0 compiler_4.1.1
[53] rlang_1.0.2 rhdf5_2.38.1 grid_4.1.1 RCurl_1.98-1.6
[57] rhdf5filters_1.6.0 rstudioapi_0.13 rjson_0.2.21 bitops_1.0-7
[61] testthat_3.1.3 restfulr_0.0.13 curl_4.3.2 R6_2.5.1
[65] GenomicAlignments_1.30.0 rtracklayer_1.54.0 fastmap_1.1.0 rprojroot_2.0.3
[69] permute_0.9-7 desc_1.4.1 parallel_4.1.1 Rcpp_1.0.8.3
[73] sparseMatrixStats_1.6.0

Bioconductor version '3.14'

• 0 packages out-of-date
• 1 packages too new

create a valid installation with

BiocManager::install("methylSig", update = TRUE, ask = FALSE)

more details: BiocManager::valid()$too_new, BiocManager::valid()$out_of_date

sessionInfo()
R version 4.1.1 (2021-08-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.4 LTS

Matrix products: default
BLAS/LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.8.so

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

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

other attached packages:
[1] bsseq_1.30.0 SummarizedExperiment_1.24.0 Biobase_2.54.0 MatrixGenerics_1.6.0
[5] matrixStats_0.61.0 GenomicRanges_1.46.1 GenomeInfoDb_1.30.1 IRanges_2.28.0
[9] S4Vectors_0.32.4 BiocGenerics_0.40.0 methylSig_1.7.0 BiocManager_1.30.16

loaded via a namespace (and not attached):
[1] pkgload_1.2.4 splines_4.1.1 R.utils_2.11.0 DelayedMatrixStats_1.16.0
[5] gtools_3.9.2 brio_1.1.3 Rsamtools_2.10.0 BSgenome_1.62.0
[9] GenomeInfoDbData_1.2.7 yaml_2.3.5 remotes_2.4.2 sessioninfo_1.2.2
[13] lattice_0.20-45 glue_1.6.2 limma_3.50.1 XVector_0.34.0
[17] colorspace_2.0-3 R.oo_1.24.0 Matrix_1.4-1 XML_3.99-0.9
[21] devtools_2.4.3 DSS_2.42.0 zlibbioc_1.40.0 purrr_0.3.4
[25] scales_1.1.1 processx_3.5.3 HDF5Array_1.22.1 BiocParallel_1.28.3
[29] usethis_2.1.5 ellipsis_0.3.2 cachem_1.0.6 withr_2.5.0
[33] cli_3.2.0 magrittr_2.0.3 crayon_1.5.1 memoise_2.0.1
[37] ps_1.6.0 R.methodsS3_1.8.1 fs_1.5.2 pkgbuild_1.3.1
[41] tools_4.1.1 data.table_1.14.2 prettyunits_1.1.1 BiocIO_1.4.0
[45] lifecycle_1.0.1 Rhdf5lib_1.16.0 munsell_0.5.0 locfit_1.5-9.5
[49] DelayedArray_0.20.0 callr_3.7.0 Biostrings_2.62.0 compiler_4.1.1
[53] rlang_1.0.2 rhdf5_2.38.1 grid_4.1.1 RCurl_1.98-1.6
[57] rhdf5filters_1.6.0 rstudioapi_0.13 rjson_0.2.21 bitops_1.0-7
[61] testthat_3.1.3 restfulr_0.0.13 curl_4.3.2 R6_2.5.1
[65] GenomicAlignments_1.30.0 rtracklayer_1.54.0 fastmap_1.1.0 rprojroot_2.0.3
[69] permute_0.9-7 desc_1.4.1 parallel_4.1.1 Rcpp_1.0.8.3
[73] sparseMatrixStats_1.6.0

[PeteHaitch]

If you share an example file rather than a screenshot it'll be easier to help you