the supplied seed must support extract_array() #125
Description
I am trying to have some reproducibility using docker containers for scRNAseq analysis.
Unfortunately the data I am trying to analyze are quite large thus I need to use some aws services.
For this reason I used rds objects and a locally built container. Iuploaded everything on aws and run the large data analysis.
Every time I try to subset the singlecellexperiment object I get this issue:
> neu.sub <- neu.sce[, cell_s$cell_label]
Loading required namespace: HDF5Array
Error in validObject(.Object) : invalid class "DelayedSubset" object:
the supplied seed must support extract_array()
The only time I didn't get the error was when I made the object inside the container, saved as rds (in the container volume mounted on my local machine), loaded it again on the container and I could subset without error.
Instead when I used a previous (almost the same object saved locally as .rds) made on my machine (not in the container) and loaded in the container, on the subsetting I got the same error.
At first I thought that it was some incompatibility of R version / package version. Now I have used the object made inside the container from my machine and load it inside the same container on aws instance and getting that error.
The data are public so I can share the code if needed for reproducibility.
Regarding the image of the container I can send (?upload?) somewhere the tar image that can be loaded (amd64) with docker load -i image.tar
Where should I start searching to debug this issue?
> sessionInfo()
R version 4.5.1 (2025-06-13)
Platform: x86_64-pc-linux-gnu
Running under: Debian GNU/Linux 13 (trixie)
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.1
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1; LAPACK version 3.12.0
locale:
[1] C
time zone: Etc/UTC
tzcode source: system (glibc)
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] bluster_1.18.0 zellkonverter_1.18.0
[3] scran_1.36.0 scater_1.36.0
[5] ggplot2_4.0.0 scuttle_1.18.0
[7] SingleCellExperiment_1.30.1 SingleR_2.10.0
[9] SummarizedExperiment_1.38.1 Biobase_2.68.0
[11] GenomicRanges_1.60.0 GenomeInfoDb_1.44.3
[13] IRanges_2.42.0 S4Vectors_0.46.0
[15] BiocGenerics_0.54.0 generics_0.1.4
[17] MatrixGenerics_1.20.0 matrixStats_1.5.0
[19] openxlsx_4.2.8 vroom_1.6.6
[21] rlang_1.1.6 stringr_1.5.2
[23] tibble_3.3.0 dplyr_1.1.4
[25] tidyr_1.3.1 readr_2.1.5
[27] here_1.0.2
loaded via a namespace (and not attached):
[1] gridExtra_2.3 magrittr_2.0.4
[3] compiler_4.5.1 dir.expiry_1.16.0
[5] DelayedMatrixStats_1.30.0 png_0.1-8
[7] vctrs_0.6.5 pkgconfig_2.0.3
[9] crayon_1.5.3 XVector_0.48.0
[11] tzdb_0.5.0 UCSC.utils_1.4.0
[13] ggbeeswarm_0.7.2 purrr_1.1.0
[15] bit_4.6.0 beachmat_2.24.0
[17] jsonlite_2.0.0 rhdf5filters_1.20.0
[19] DelayedArray_0.34.1 Rhdf5lib_1.30.0
[21] BiocParallel_1.42.2 irlba_2.3.5.1
[23] parallel_4.5.1 cluster_2.1.8.1
[25] R6_2.6.1 stringi_1.8.7
[27] RColorBrewer_1.1-3 limma_3.64.3
[29] reticulate_1.43.0 Rcpp_1.1.0
[31] Matrix_1.7-3 igraph_2.1.4
[33] tidyselect_1.2.1 abind_1.4-8
[35] viridis_0.6.5 codetools_0.2-20
[37] lattice_0.22-7 basilisk.utils_1.20.0
[39] withr_3.0.2 S7_0.2.0
[41] zip_2.3.3 pillar_1.11.1
[43] filelock_1.0.3 rprojroot_2.1.1
[45] hms_1.1.3 sparseMatrixStats_1.20.0
[47] scales_1.4.0 glue_1.8.0
[49] metapod_1.16.0 tools_4.5.1
[51] BiocNeighbors_2.2.0 ScaledMatrix_1.16.0
[53] locfit_1.5-9.12 rhdf5_2.52.1
[55] grid_4.5.1 edgeR_4.6.3
[57] GenomeInfoDbData_1.2.14 basilisk_1.20.0
[59] beeswarm_0.4.0 BiocSingular_1.24.0
[61] HDF5Array_1.36.0 vipor_0.4.7
[63] cli_3.6.5 rsvd_1.0.5
[65] S4Arrays_1.8.1 viridisLite_0.4.2
[67] gtable_0.3.6 SparseArray_1.8.1
[69] ggrepel_0.9.6 dqrng_0.4.1
[71] farver_2.1.2 lifecycle_1.0.4
[73] h5mread_1.0.1 httr_1.4.7
[75] statmod_1.5.1 bit64_4.6.0-1
Maybe related? #112