Entering edit mode
Hi all,
I am running DESeq2 on a Unix cluster and exporting the result onto my laptop using scp transfer for further analyses. Using R, I save the result of DESeq2 as an R object (Robj):
dds <- DESeq(dds, sfType = "poscounts", useT = TRUE, minmu = 1e-6)
save(dds, file = "/cluster/path/to/file/dds.Robj")
dds
class: DESeqDataSet
dim: 3807 79
metadata(1): version
assays(7): counts weights ... replaceCounts replaceCooks
rownames(3807): 14-3-3epsilon 14-3-3zeta ... zip zld
rowData names(32): baseMean baseVar ... tDegreesFreedom replace
colnames(79): dep06_rep1_GCCATGGCACAGAGCA dep06_rep1_GCAGCTGGTCAATGGG ...
sat00_rep2_TGGGAGACAGGCTACC sat00_rep2_CCTTTGGGTTCCTAAG
colData names(54): orig.ident nCount_RNA ... sizeFactor replaceable
So far so good. Now I use scp to transfer the file to my computer:
scp name@domain.extension:/cluster/path/to/file/dds.Robj /local/path/to/file/.
And load it into R locally:
load("/local/path/to/file/dds.Robj)
Now when I open the file in R, I would expect to see a summary of the dds object, as above, but instead I get the following error:
dds
class: DESeqDataSet
dim:
metadata(1): version
Error in getClass(element.type) : “SimpleAssays” is not a defined class
Error during wrapup: 'length(x) = 14 > 1' in coercion to 'logical(1)'
If I run DESeq2 on my laptop there is no problem, and if I copy the file back onto the server there is no problem either...
Does anyone have an idea of what is going on and how I could fix this? Many thanks, Vinnie
Session Info (Cluster):
R version 3.6.1 (2019-07-05)
Platform: x86_64-conda_cos6-linux-gnu (64-bit)
Running under: Scientific Linux release 6.10 (Carbon)
Matrix products: default
BLAS/LAPACK: /ifs/home/vincent/.conda/envs/zinb/lib/R/lib/libRblas.so
locale:
[1] LC_CTYPE=en_GB.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_GB.UTF-8 LC_COLLATE=en_GB.UTF-8
[5] LC_MONETARY=en_GB.UTF-8 LC_MESSAGES=en_GB.UTF-8
[7] LC_PAPER=en_GB.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] parallel stats4 tcltk stats graphics grDevices utils
[8] datasets methods base
other attached packages:
[1] ashr_2.2-39 lmtest_0.9-37
[3] zoo_1.8-6 apeglm_1.8.0
[5] zinbwave_1.8.0 gsl_2.1-6
[7] MAST_1.12.0 SingleCellExperiment_1.8.0
[9] scales_1.0.0 DECENT_1.1.0
[11] edgeR_3.28.0 limma_3.42.0
[13] DESeq2_1.26.0 SummarizedExperiment_1.16.0
[15] DelayedArray_0.12.0 BiocParallel_1.20.0
[17] matrixStats_0.55.0 Biobase_2.46.0
[19] GenomicRanges_1.38.0 GenomeInfoDb_1.22.0
[21] IRanges_2.20.0 S4Vectors_0.24.0
[23] BiocGenerics_0.32.0 lattice_0.20-38
[25] data.table_1.12.6 RColorBrewer_1.1-2
[27] dplyr_0.8.3 Seurat_3.1.1
[29] cowplot_1.0.0 Matrix_1.2-17
[31] ggplot2_3.2.1
loaded via a namespace (and not attached):
[1] backports_1.1.5 Hmisc_4.2-0 VGAM_1.1-1
[4] plyr_1.8.4 igraph_1.2.4.1 lazyeval_0.2.2
[7] splines_3.6.1 listenv_0.7.0 digest_0.6.22
[10] foreach_1.4.7 htmltools_0.4.0 SQUAREM_2017.10-1
[13] gdata_2.18.0 magrittr_1.5 checkmate_1.9.4
[16] memoise_1.1.0 doParallel_1.0.15 cluster_2.1.0
[19] ROCR_1.0-7 globals_0.12.4 annotate_1.64.0
[22] RcppParallel_4.4.4 R.utils_2.9.0 colorspace_1.4-1
[25] blob_1.2.0 ggrepel_0.8.1 xfun_0.10
[28] crayon_1.3.4 RCurl_1.95-4.12 jsonlite_1.6
[31] genefilter_1.68.0 zeallot_0.1.0 iterators_1.0.12
[34] survival_3.1-6 ape_5.3 glue_1.3.1
[37] gtable_0.3.0 zlibbioc_1.32.0 XVector_0.26.0
[40] leiden_0.3.1 future.apply_1.3.0 pscl_1.5.2
[43] abind_1.4-5 DBI_1.0.0 bibtex_0.4.2
[46] Rcpp_1.0.3 metap_1.1 emdbook_1.3.11
[49] viridisLite_0.3.0 xtable_1.8-4 htmlTable_1.13.2
[52] reticulate_1.13 foreign_0.8-72 bit_1.1-14
[55] rsvd_1.0.2 SDMTools_1.1-221.1 Formula_1.2-3
[58] tsne_0.1-3 truncnorm_1.0-8 htmlwidgets_1.5.1
[61] httr_1.4.1 gplots_3.0.1.1 acepack_1.4.1
[64] ica_1.0-2 pkgconfig_2.0.3 XML_3.98-1.20
[67] R.methodsS3_1.7.1 nnet_7.3-12 uwot_0.1.4
[70] locfit_1.5-9.1 softImpute_1.4 tidyselect_0.2.5
[73] rlang_0.4.1 reshape2_1.4.3 AnnotationDbi_1.48.0
[76] munsell_0.5.0 tools_3.6.1 RSQLite_2.1.2
[79] ggridges_0.5.1 stringr_1.4.0 npsurv_0.4-0
[82] knitr_1.25 bit64_0.9-7 fitdistrplus_1.0-14
[85] caTools_1.17.1.2 purrr_0.3.3 RANN_2.6.1
[88] pbapply_1.4-2 future_1.14.0 nlme_3.1-141
[91] R.oo_1.23.0 compiler_3.6.1 rstudioapi_0.10
[94] plotly_4.9.0 png_0.1-7 lsei_1.2-0
[97] statmod_1.4.32 tibble_2.1.3 geneplotter_1.64.0
[100] stringi_1.4.3 ZIM_1.1.0 vctrs_0.2.0
[103] pillar_1.4.2 lifecycle_0.1.0 Rdpack_0.11-0
[106] RcppAnnoy_0.0.13 bitops_1.0-6 irlba_2.3.3
[109] gbRd_0.4-11 R6_2.4.0 latticeExtra_0.6-28
[112] KernSmooth_2.23-16 gridExtra_2.3 codetools_0.2-16
[115] MASS_7.3-51.4 gtools_3.8.1 assertthat_0.2.1
[118] withr_2.1.2 sctransform_0.2.0 GenomeInfoDbData_1.2.2
[121] grid_3.6.1 rpart_4.1-15 coda_0.19-3
[124] tidyr_1.0.0 Rtsne_0.15 mixsqp_0.2-2
[127] bbmle_1.0.20 numDeriv_2016.8-1.1 base64enc_0.1-3
Session Info (Local):
R version 3.6.1 (2019-07-05)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Catalina 10.15.2
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
Random number generation:
RNG: Mersenne-Twister
Normal: Inversion
Sample: Rounding
locale:
[1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8
attached base packages:
[1] parallel stats4 tcltk stats graphics grDevices utils datasets methods base
other attached packages:
[1] yaml_2.2.0 R.utils_2.9.0 R.oo_1.23.0
[4] R.methodsS3_1.7.1 bit64_0.9-7 bit_1.1-14
[7] ashr_2.2-39 lmtest_0.9-37 zoo_1.8-6
[10] apeglm_1.6.0 zinbwave_1.6.0 gsl_1.9-10.3
[13] MAST_1.10.0 SingleCellExperiment_1.6.0 scales_1.0.0
[16] DECENT_1.1.0 edgeR_3.26.8 limma_3.40.6
[19] DESeq2_1.24.0 SummarizedExperiment_1.14.1 DelayedArray_0.10.0
[22] BiocParallel_1.18.1 matrixStats_0.55.0 Biobase_2.44.0
[25] GenomicRanges_1.36.1 GenomeInfoDb_1.20.0 IRanges_2.18.3
[28] S4Vectors_0.22.1 BiocGenerics_0.30.0 DoubletFinder_2.0.2
[31] clustree_0.4.1 ggraph_2.0.0 lattice_0.20-38
[34] heatmap3_1.1.6 data.table_1.12.6 RColorBrewer_1.1-2
[37] randomcoloR_1.1.0 dplyr_0.8.3 Seurat_3.1.1
[40] cowplot_1.0.0 Matrix_1.2-17 ggplot2_3.2.1
loaded via a namespace (and not attached):
[1] reticulate_1.13 tidyselect_0.2.5 lme4_1.1-21 RSQLite_2.1.2
[5] AnnotationDbi_1.46.1 htmlwidgets_1.5.1 grid_3.6.1 Rtsne_0.15
[9] munsell_0.5.0 codetools_0.2-16 ica_1.0-2 statmod_1.4.32
[13] future_1.15.0 withr_2.1.2 colorspace_1.4-1 knitr_1.26
[17] pspline_1.0-18 rstudioapi_0.10 pscl_1.5.2 ROCR_1.0-7
[21] gbRd_0.4-11 listenv_0.7.0 labeling_0.3 Rdpack_0.11-0
[25] bbmle_1.0.20 GenomeInfoDbData_1.2.1 mixsqp_0.2-2 polyclip_1.10-0
[29] farver_2.0.1 coda_0.19-3 vctrs_0.2.0 xfun_0.11
[33] fastcluster_1.1.25 R6_2.4.1 doParallel_1.0.15 graphlayouts_0.5.0
[37] rsvd_1.0.2 VGAM_1.1-1 locfit_1.5-9.1 bitops_1.0-6
[41] assertthat_0.2.1 SDMTools_1.1-221.1 nnet_7.3-12 ZIM_1.1.0
[45] gtable_0.3.0 npsurv_0.4-0 globals_0.12.4 tidygraph_1.1.2
[49] rlang_0.4.1 zeallot_0.1.0 genefilter_1.66.0 splines_3.6.1
[53] lazyeval_0.2.2 acepack_1.4.1 checkmate_1.9.4 reshape2_1.4.3
[57] abind_1.4-5 backports_1.1.5 Hmisc_4.3-0 tools_3.6.1
[61] gplots_3.0.1.1 stabledist_0.7-1 ggridges_0.5.1 Rcpp_1.0.3
[65] plyr_1.8.4 base64enc_0.1-3 zlibbioc_1.30.0 purrr_0.3.3
[69] RCurl_1.95-4.12 rpart_4.1-15 pbapply_1.4-2 viridis_0.5.1
[73] ggrepel_0.8.1 cluster_2.1.0 magrittr_1.5 RANN_2.6.1
[77] truncnorm_1.0-8 SQUAREM_2017.10-1 mvtnorm_1.0-11 fitdistrplus_1.0-14
[81] lsei_1.2-0 xtable_1.8-4 XML_3.98-1.20 emdbook_1.3.11
[85] shape_1.4.4 gridExtra_2.3 compiler_3.6.1 tibble_2.1.3
[89] KernSmooth_2.23-16 V8_2.3 crayon_1.3.4 minqa_1.2.4
[93] htmltools_0.4.0 pcaPP_1.9-73 Formula_1.2-3 tidyr_1.0.0
[97] geneplotter_1.62.0 RcppParallel_4.4.4 DBI_1.0.0 tweenr_1.0.1
[101] MASS_7.3-51.4 boot_1.3-23 gdata_2.18.0 metap_1.1
[105] igraph_1.2.4.1 pkgconfig_2.0.3 numDeriv_2016.8-1.1 foreign_0.8-72
[109] plotly_4.9.1 foreach_1.4.7 annotate_1.62.0 blme_1.0-4
[113] XVector_0.24.0 bibtex_0.4.2 stringr_1.4.0 digest_0.6.22
[117] copula_0.999-19.1 sctransform_0.2.0 RcppAnnoy_0.0.14 tsne_0.1-3
[121] ADGofTest_0.3 softImpute_1.4 leiden_0.3.1 htmlTable_1.13.2
[125] uwot_0.1.4 curl_4.2 gtools_3.8.1 nloptr_1.2.1
[129] lifecycle_0.1.0 nlme_3.1-142 jsonlite_1.6 viridisLite_0.3.0
[133] pillar_1.4.2 httr_1.4.1 survival_3.1-7 glue_1.3.1
[137] png_0.1-7 iterators_1.0.12 glmnet_3.0-1 ggforce_0.3.1
[141] stringi_1.4.3 blob_1.2.0 latticeExtra_0.6-28 caTools_1.17.1.2
[145] memoise_1.1.0 irlba_2.3.3 future.apply_1.3.0 ape_5.3
It looks like your laptop is at an older version of Bioconductor than the cluster; confirm this with
It seems likely that you can update your laptop to a current version with (in a new R session, with no packages attached)
Yeah that works, thanks a lot!