Error in .Call2("C_find_overlaps_in_groups_NCList", start(q), end(q),

[Muchmorepig]

txdb <- txdbmaker::makeTxDbFromGFF("/data/corum.gtf", format = "gtf")

# Import genomic features from the file as a GRanges object ... OK
# Prepare the 'metadata' data frame ... OK
Make the TxDb object ... Error in .Call2("C_find_overlaps_in_groups_NCList", start(q), end(q),  : 
  build_NCList: memory allocation failed

R.version
_
platform x86_64-pc-linux-gnu
arch x86_64
os linux-gnu
system x86_64, linux-gnu
status
major 4
minor 4.0
year 2024
month 04
day 24
svn rev 86474
language R
version.string R version 4.4.0 (2024-04-24)
nickname Puppy Cup

[hpages]

Why open the issue in the GenomicFeatures repos when this is an issue with makeTxDbFromGFF() from the txdbmaker package?

Also we need a reproducible example in order to act on this. Where is the corum.gtf file?

Please provide the output of your sessionInfo().

Thanks!

[Muchmorepig]

sorry, because it occurs when i use GenomicFeatures and i did not find other repos
GFF3: http://v2.insect-genome.com/api/Download/..-01_data-01_species-Apolygus_lucorum-Apolygus_lucorum.gff3
here is my sessionInfo, thanks

sessionInfo()
R version 4.4.0 (2024-04-24)
Platform: x86_64-pc-linux-gnu
Running under: Ubuntu 20.04.6 LTS

Matrix products: default
BLAS/LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.8.so; LAPACK version 3.9.0

locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8
[6] LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_US.UTF-8 LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

time zone: Asia/Shanghai
tzcode source: system (glibc)

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

other attached packages:
[1] GenomicFeatures_1.58.0 AnnotationDbi_1.68.0 Biobase_2.64.0 GenomicRanges_1.56.1 GenomeInfoDb_1.40.1 IRanges_2.38.1
[7] S4Vectors_0.44.0 BiocGenerics_0.52.0

loaded via a namespace (and not attached):
[1] KEGGREST_1.44.1 SummarizedExperiment_1.34.0 rjson_0.2.23 httr2_1.0.7 lattice_0.22-6
[6] generics_0.1.3 vctrs_0.6.5 tools_4.4.0 bitops_1.0-7 curl_6.0.1
[11] parallel_4.4.0 tibble_3.2.1 RSQLite_2.3.7 blob_1.2.4 pkgconfig_2.0.3
[16] Matrix_1.7-0 dbplyr_2.5.0 lifecycle_1.0.4 GenomeInfoDbData_1.2.12 compiler_4.4.0
[21] stringr_1.5.1 Rsamtools_2.20.0 Biostrings_2.72.1 progress_1.2.3 codetools_0.2-20
[26] RCurl_1.98-1.16 yaml_2.3.8 pillar_1.10.0 crayon_1.5.2 BiocParallel_1.40.0
[31] DelayedArray_0.32.0 cachem_1.1.0 abind_1.4-5 tidyselect_1.2.1 digest_0.6.35
[36] stringi_1.8.4 dplyr_1.1.4.9000 restfulr_0.0.15 biomaRt_2.62.0 fastmap_1.2.0
[41] grid_4.4.0 cli_3.6.3 SparseArray_1.6.0 magrittr_2.0.3 S4Arrays_1.6.0
[46] XML_3.99-0.17 filelock_1.0.3 prettyunits_1.2.0 UCSC.utils_1.0.0 rappdirs_0.3.3
[51] bit64_4.0.5 XVector_0.44.0 httr_1.4.7 matrixStats_1.3.0 bit_4.0.5
[56] png_0.1-8 hms_1.1.3 memoise_2.0.1 BiocIO_1.14.0 BiocFileCache_2.14.0
[61] rtracklayer_1.64.0 txdbmaker_1.2.1 rlang_1.1.4 glue_1.8.0 DBI_1.2.3
[66] xml2_1.3.6 rstudioapi_0.16.0 jsonlite_1.8.8 R6_2.5.1 MatrixGenerics_1.16.0
[71] GenomicAlignments_1.40.0 zlibbioc_1.50.0

[hpages]

sorry, because it occurs when i use GenomicFeatures and i did not find other repos

It doesn't seem that way. The error occurs when you are explicitly calling txdbmaker::makeTxDbFromGFF() (this is your code, not mine). You realize that the txdbmaker:: syntax means that you are calling a function defined in the txdbmaker package right?

Now you gave me a link to a GFF3 file (thanks for sharing the file). However, your initial code is trying to import a GTF file. Did you use a tool to convert the file from GFF3 to GTF? I'm confused! Again, it would be useful if you could take the time to provide a standalone reproducible example, that is, code that shows exactly what you did. No hidden steps please! That way I don't have to guess.

Thanks!

[shuaifengwang]

I encountered the same error problem, have you solved it?

[hpages]

@shuaifengwang You're not providing any information about what you are doing hence we cannot help you. Please provide a minimal reproducible example (MRE). Also show the output produced by sessionInfo() after you run the MRE. Thanks!

[shuaifengwang]

when i use the code to generate txdb file, the error was occured, my code:

library(ChIPseeker)
library(GenomicFeatures)
library(txdbmaker)
txdb <- makeTxDbFromGFF("hg38.knownGene.gtf",
format = 'gtf',organism = "Homo sapiens")

Make the TxDb object ... Error in .Call2("C_find_overlaps_in_groups_NCList", start(q), end(q), :
build_NCList: memory allocation failed
In addition: Warning message:
In .get_cds_IDX(mcols0$type, mcols0$phase) :
The "phase" metadata column contains non-NA values for features of type
stop_codon. This information was ignored.

sessioninfo()
R version 4.4.1 (2024-06-14)
Platform: x86_64-pc-linux-gnu
Running under: Ubuntu 24.04.1 LTS

Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.0

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

time zone: Asia/Shanghai
tzcode source: system (glibc)

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

other attached packages:
[1] clusterProfiler_4.12.6 TxDb.Hsapiens.UCSC.hg38.knownGene_3.4.0
[3] txdbmaker_1.2.1 GenomicFeatures_1.58.0
[5] AnnotationDbi_1.70.0 Biobase_2.64.0
[7] GenomicRanges_1.56.1 GenomeInfoDb_1.40.1
[9] IRanges_2.38.1 S4Vectors_0.44.0
[11] BiocGenerics_0.52.0 ChIPseeker_1.45.0

loaded via a namespace (and not attached):
[1] RColorBrewer_1.1-3 rstudioapi_0.17.1
[3] jsonlite_2.0.0 magrittr_2.0.3
[5] farver_2.1.2 fs_1.6.6
[7] BiocIO_1.16.0 zlibbioc_1.50.0
[9] vctrs_0.6.5 memoise_2.0.1
[11] Rsamtools_2.20.0 RCurl_1.98-1.17
[13] ggtree_3.12.0 progress_1.2.3
[15] S4Arrays_1.6.0 TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
[17] plotrix_3.8-4 curl_6.4.0
[19] SparseArray_1.6.0 gridGraphics_0.5-1
[21] KernSmooth_2.23-24 plyr_1.8.9
[23] httr2_1.1.2 cachem_1.1.0
[25] GenomicAlignments_1.42.0 igraph_2.1.4
[27] lifecycle_1.0.4 pkgconfig_2.0.3
[29] gson_0.1.0 Matrix_1.7-0
[31] R6_2.6.1 fastmap_1.2.0
[33] GenomeInfoDbData_1.2.12 MatrixGenerics_1.16.0
[35] digest_0.6.37 aplot_0.2.7
[37] enrichplot_1.24.4 colorspace_2.1-1
[39] patchwork_1.3.1 RSQLite_2.4.1
[41] filelock_1.0.3 httr_1.4.7
[43] polyclip_1.10-7 abind_1.4-8
[45] compiler_4.4.1 bit64_4.6.0-1
[47] withr_3.0.2 BiocParallel_1.38.0
[49] viridis_0.6.5 DBI_1.2.3
[51] ggforce_0.5.0 gplots_3.2.0
[53] R.utils_2.13.0 biomaRt_2.62.0
[55] MASS_7.3-61 rappdirs_0.3.3
[57] DelayedArray_0.32.0 rjson_0.2.23
[59] caTools_1.18.3 gtools_3.9.5
[61] tools_4.4.1 ape_5.8-1
[63] scatterpie_0.2.5 R.oo_1.27.1
[65] glue_1.8.0 restfulr_0.0.15
[67] nlme_3.1-165 GOSemSim_2.30.2
[69] grid_4.4.1 shadowtext_0.1.4
[71] reshape2_1.4.4 fgsea_1.30.0
[73] generics_0.1.4 gtable_0.3.6
[75] R.methodsS3_1.8.2 tidyr_1.3.1
[77] hms_1.1.3 data.table_1.17.6
[79] xml2_1.3.8 tidygraph_1.3.1
[81] XVector_0.44.0 ggrepel_0.9.6
[83] pillar_1.10.2 stringr_1.5.1
[85] yulab.utils_0.2.0 splines_4.4.1
[87] dplyr_1.1.4 tweenr_2.0.3
[89] BiocFileCache_2.14.0 treeio_1.28.0
[91] lattice_0.22-5 rtracklayer_1.66.0
[93] bit_4.6.0 tidyselect_1.2.1
[95] GO.db_3.19.1 Biostrings_2.72.1
[97] gridExtra_2.3 SummarizedExperiment_1.34.0
[99] graphlayouts_1.2.2 matrixStats_1.5.0
[101] stringi_1.8.7 UCSC.utils_1.0.0
[103] lazyeval_0.2.2 ggfun_0.1.9
[105] yaml_2.3.10 boot_1.3-30
[107] codetools_0.2-20 ggraph_2.2.1
[109] tibble_3.3.0 qvalue_2.36.0
[111] ggplotify_0.1.2 cli_3.6.5
[113] Rcpp_1.0.14 dbplyr_2.5.0
[115] png_0.1-8 XML_3.99-0.18
[117] ggplot2_3.5.2 blob_1.2.4
[119] prettyunits_1.2.0 DOSE_3.30.5
[121] bitops_1.0-9 viridisLite_0.4.2
[123] tidytree_0.4.6 scales_1.4.0
[125] purrr_1.0.4 crayon_1.5.3
[127] rlang_1.1.6 cowplot_1.1.3
[129] fastmatch_1.1-6 KEGGREST_1.44.1

otherwise, when i used my code to generate peakanno, the error came again:
N_I.up.anno=annotatePeak(N_I.up, tssRegion=c(-3000, 3000),
TxDb=txdb, annoDb="org.Hs.eg.db")

Error in .Call2("C_find_overlaps_in_groups_NCList", start(q), end(q), :
build_NCList: memory allocation failed

Have you encountered similar problems before and how should you handle them？

[xuzishu0613-tech]

txdb <- txdbmaker::makeTxDbFromGFF("/data/corum.gtf", format = "gtf")

Import genomic features from the file as a GRanges object ... OK

Prepare the 'metadata' data frame ... OK

Make the TxDb object ... Error in .Call2("C_find_overlaps_in_groups_NCList", start(q), end(q), :
build_NCList: memory allocation failed

R.version _ platform x86_64-pc-linux-gnu arch x86_64 os linux-gnu system x86_64, linux-gnu status major 4 minor 4.0 year 2024 month 04 day 24 svn rev 86474 language R version.string R version 4.4.0 (2024-04-24) nickname Puppy Cup

Hello, I ran into the same problem. Have you managed to solve it?
你好，我遇到了相同的问题，之前用的时候都没有这个问题，很奇怪不知道为何今天运行的时候出现了，请问你解决了吗？

library(tidyverse)

library(ChIPseeker)
library(GenomicFeatures)
library(txdbmaker)

正确的 TxDb 生成方式

txdb <- txdbmaker::makeTxDbFromGFF("ref/IWGSC_v1.1_HC_20170706.gtf", format="gtf")
Import genomic features from the file as a GRanges object ... OK
Prepare the 'metadata' data frame ... OK
Make the TxDb object ... Error in .Call2("C_find_overlaps_in_groups_NCList", start(q), end(q), :
build_NCList: memory allocation failed
sessionInfo()
R version 4.4.1 (2024-06-14)
Platform: x86_64-pc-linux-gnu
Running under: Ubuntu 22.04.5 LTS

Matrix products: default
BLAS/LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so; LAPACK version 3.10.0

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

time zone: Asia/Shanghai
tzcode source: system (glibc)

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

other attached packages:
[1] rtracklayer_1.64.0 txdbmaker_1.0.1 GenomicFeatures_1.56.0 AnnotationDbi_1.66.0
[5] Biobase_2.66.0 GenomicRanges_1.56.2 GenomeInfoDb_1.40.1 IRanges_2.38.1
[9] S4Vectors_0.44.0 BiocGenerics_0.52.0 ChIPseeker_1.40.0 lubridate_1.9.4
[13] forcats_1.0.0 stringr_1.6.0 dplyr_1.1.4 purrr_1.2.0
[17] readr_2.1.5 tidyr_1.3.1 tibble_3.2.1 ggplot2_3.5.2
[21] tidyverse_2.0.0

loaded via a namespace (and not attached):
[1] RColorBrewer_1.1-3 rstudioapi_0.17.1
[3] jsonlite_2.0.0 magrittr_2.0.4
[5] farver_2.1.2 fs_1.6.6
[7] BiocIO_1.14.0 zlibbioc_1.52.0
[9] vctrs_0.6.5 memoise_2.0.1
[11] Rsamtools_2.20.0 RCurl_1.98-1.17
[13] ggtree_3.12.0 progress_1.2.3
[15] S4Arrays_1.4.1 TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
[17] plotrix_3.8-13 curl_7.0.0
[19] SparseArray_1.4.8 gridGraphics_0.5-1
[21] KernSmooth_2.23-26 plyr_1.8.9
[23] httr2_1.2.1 cachem_1.1.0
[25] GenomicAlignments_1.40.0 igraph_2.1.1
[27] lifecycle_1.0.4 pkgconfig_2.0.3
[29] Matrix_1.7-4 R6_2.6.1
[31] fastmap_1.2.0 GenomeInfoDbData_1.2.13
[33] MatrixGenerics_1.18.1 digest_0.6.39
[35] aplot_0.2.3 enrichplot_1.24.4
[37] colorspace_2.1-2 patchwork_1.3.0
[39] RSQLite_2.3.7 filelock_1.0.3
[41] timechange_0.3.0 httr_1.4.7
[43] polyclip_1.10-7 abind_1.4-8
[45] compiler_4.4.1 bit64_4.6.0-1
[47] withr_3.0.2 BiocParallel_1.40.2
[49] viridis_0.6.5 DBI_1.2.3
[51] gplots_3.2.0 ggforce_0.4.2
[53] R.utils_2.13.0 biomaRt_2.60.1
[55] MASS_7.3-65 rappdirs_0.3.3
[57] DelayedArray_0.30.1 rjson_0.2.23
[59] caTools_1.18.3 gtools_3.9.5
[61] tools_4.4.1 scatterpie_0.2.4
[63] ape_5.8 R.oo_1.27.1
[65] glue_1.8.0 restfulr_0.0.15
[67] nlme_3.1-168 GOSemSim_2.30.2
[69] shadowtext_0.1.4 grid_4.4.1
[71] reshape2_1.4.4 fgsea_1.30.0
[73] generics_0.1.4 gtable_0.3.6
[75] tzdb_0.4.0 R.methodsS3_1.8.2
[77] data.table_1.16.2 hms_1.1.4
[79] xml2_1.3.6 tidygraph_1.3.1
[81] XVector_0.44.0 ggrepel_0.9.6
[83] pillar_1.11.1 yulab.utils_0.1.8
[85] splines_4.4.1 tweenr_2.0.3
[87] BiocFileCache_2.12.0 treeio_1.28.0
[89] lattice_0.22-7 bit_4.6.0
[91] tidyselect_1.2.1 GO.db_3.19.1
[93] Biostrings_2.72.1 gridExtra_2.3
[95] SummarizedExperiment_1.34.0 graphlayouts_1.2.0
[97] matrixStats_1.5.0 stringi_1.8.7
[99] UCSC.utils_1.0.0 lazyeval_0.2.2
[101] ggfun_0.1.7 yaml_2.3.10
[103] boot_1.3-32 codetools_0.2-20
[105] ggraph_2.2.1 qvalue_2.36.0
[107] ggplotify_0.1.2 cli_3.6.3
[109] dichromat_2.0-0.1 Rcpp_1.1.0
[111] dbplyr_2.5.0 png_0.1-8
[113] XML_3.99-0.20 parallel_4.4.1
[115] blob_1.2.4 prettyunits_1.2.0
[117] DOSE_3.30.5 bitops_1.0-9
[119] tidytree_0.4.6 viridisLite_0.4.2
[121] scales_1.4.0 crayon_1.5.3
[123] rlang_1.1.6 cowplot_1.1.3
[125] fastmatch_1.1-6 KEGGREST_1.46.0

[hpages]

@xuzishu0613-tech We need a minimum reproducible example (MRE) in order to work on this. Of course we need access to the GFF or GTF file used in the MRE otherwise we cannot reproduce. None of the posters in this issue have provided this so far, so unfortunately we cannot make any progress.

In the meantime, I would recommend that you upgrade your R/Bioconductor installation to the latest versions: R 4.5 / BioC 3.22. Maybe that will help with the memory issue that you're running into.