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kokyriakidis
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@6deab231
Last seen 3.3 years ago
Hello Michael Love
When I try to run the DE analysis I get the following error. Do you have any clue why this error arise?
> ddsDE <- DESeq(ddsSE)
estimating size factors
estimating dispersions
gene-wise dispersion estimates
mean-dispersion relationship
-- note: fitType='parametric', but the dispersion trend was not well captured by the
function: y = a/x + b, and a local regression fit was automatically substituted.
specify fitType='local' or 'mean' to avoid this message next time.
final dispersion estimates
fitting model and testing
warning: solve(): system seems singular; attempting approx solution
Error in fitBeta(ySEXP = ySEXP, xSEXP = xSEXP, nfSEXP = nfSEXP, alpha_hatSEXP = alpha_hatSEXP, :
BLAS/LAPACK routine 'DGELSD' gave error code -4
> sessionInfo( )
R version 4.0.3 (2020-10-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.1 LTS
Matrix products: default
BLAS/LAPACK: /usr/lib/x86_64-linux-gnu/libmkl_rt.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=el_GR.UTF-8
[4] LC_COLLATE=en_US.UTF-8 LC_MONETARY=el_GR.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=el_GR.UTF-8 LC_NAME=C LC_ADDRESS=C
[10] LC_TELEPHONE=C LC_MEASUREMENT=el_GR.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] parallel stats4 stats graphics grDevices utils datasets methods
[9] base
other attached packages:
[1] DESeqAnalysis_0.3.10 DESeq2_1.30.0 bcbioRNASeq_0.3.39
[4] basejump_0.13.4 SummarizedExperiment_1.20.0 Biobase_2.50.0
[7] GenomicRanges_1.42.0 GenomeInfoDb_1.26.2 IRanges_2.24.1
[10] S4Vectors_0.28.1 BiocGenerics_0.36.0 MatrixGenerics_1.2.0
[13] matrixStats_0.57.0
loaded via a namespace (and not attached):
[1] colorspace_2.0-0 ellipsis_0.3.1
[3] ggridges_0.5.2 XVector_0.30.0
[5] AcidPlots_0.3.0 rstudioapi_0.13
[7] ggrepel_0.9.0 bit64_4.0.5
[9] interactiveDisplayBase_1.28.0 AnnotationDbi_1.52.0
[11] fansi_0.4.1 xml2_1.3.2
[13] splines_4.0.3 tximport_1.18.0
[15] goalie_0.4.11 geneplotter_1.68.0
[17] knitr_1.30 Rsamtools_2.6.0
[19] annotate_1.68.0 dbplyr_2.0.0
[21] pheatmap_1.0.12 shiny_1.5.0
[23] BiocManager_1.30.10 readr_1.4.0
[25] compiler_4.0.3 httr_1.4.2
[27] assertthat_0.2.1 Matrix_1.2-18
[29] fastmap_1.0.1 lazyeval_0.2.2
[31] limma_3.46.0 cli_2.2.0
[33] later_1.1.0.1 htmltools_0.5.0
[35] prettyunits_1.1.1 tools_4.0.3
[37] gtable_0.3.0 glue_1.4.2
[39] GenomeInfoDbData_1.2.4 dplyr_1.0.2
[41] rappdirs_0.3.1 tinytex_0.28
[43] Rcpp_1.0.5 vctrs_0.3.6
[45] AcidGenomes_0.1.1 Biostrings_2.58.0
[47] AcidGenerics_0.4.1 rtracklayer_1.50.0
[49] xfun_0.19 stringr_1.4.0
[51] syntactic_0.4.3 mime_0.9
[53] lifecycle_0.2.0 ensembldb_2.14.0
[55] XML_3.99-0.5 edgeR_3.32.0
[57] AnnotationHub_2.22.0 zlibbioc_1.36.0
[59] scales_1.1.1 vroom_1.3.2
[61] hms_0.5.3 promises_1.1.1
[63] ProtGenerics_1.22.0 AnnotationFilter_1.14.0
[65] RColorBrewer_1.1-2 SingleCellExperiment_1.12.0
[67] yaml_2.2.1 curl_4.3
[69] memoise_1.1.0 gridExtra_2.3
[71] ggplot2_3.3.2 UpSetR_1.4.0
[73] biomaRt_2.46.0 stringi_1.5.3
[75] RSQLite_2.2.1 genefilter_1.72.0
[77] BiocVersion_3.12.0 GenomicFeatures_1.42.1
[79] BiocParallel_1.24.1 rlang_0.4.9
[81] pkgconfig_2.0.3 bitops_1.0-6
[83] lattice_0.20-41 purrr_0.3.4
[85] GenomicAlignments_1.26.0 cowplot_1.1.0
[87] bit_4.0.4 tidyselect_1.1.0
[89] plyr_1.8.6 magrittr_2.0.1
[91] AcidPlyr_0.1.4 R6_2.5.0
[93] generics_0.1.0 DelayedArray_0.16.0
[95] DBI_1.1.0 pillar_1.4.7
[97] withr_2.3.0 survival_3.2-7
[99] RCurl_1.98-1.2 bcbioBase_0.6.16
[101] tibble_3.0.4 pipette_0.4.22
[103] crayon_1.3.4 BiocFileCache_1.14.0
[105] progress_1.2.2 locfit_1.5-9.4
[107] grid_4.0.3 data.table_1.13.4
[109] blob_1.2.1 digest_0.6.27
[111] xtable_1.8-4 AcidBase_0.2.6
[113] httpuv_1.5.4 openssl_1.4.3
[115] munsell_0.5.0 sessioninfo_1.1.1
[117] askpass_1.1
Michael Love Yes they are typical RNASeq data
Am I doing somehting wrong?
I do not know what the problem is but it works on my Macbook just fine. I encountered the problem on my Linux workstation only.
That is strange. The design looks fine.
One technique would be to pre-filter problemsome genes with:
Where X could be chosen as the smallest group size, i.e. number of samples in the smaller group of the design.
Michael Love It seems that I get this error in certain runs only. The problem occurs when I have many samples (eg 74 and 144 in my case). In other runs with fewer samples it works fine.
I tried what you proposed but I get the same error again. Do you have any other advice?
EDIT:
It somehow WORKS in my Macbook! I do not know what is going on. There is definitely a bug in UBUNTU 20.04. I made a fresh install of R but the issue is not resolved! I do not know if you can somehow fix it, but keep this issue in mind for Ubuntu 20.04.
Thanks for the update. I suppose if other users encounter this, they can bump the thread, but I haven't been able to reproduce on my end.
Updating Deseq2 1.32.0 error was no longer an issue. May be an issue when using 1.30.1