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Guido Hooiveld
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@guido-hooiveld-2020
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Wageningen University, Wageningen, the …
A fresh Linux install of R crashes/segfaults when fitting a probelevel model using oligo
on a dataset. Is this a bug? If not, any idea how to fix this? I don't know whether it is important, but please note that R is configured to use multi threaded OpenBLAS (rather than the default single-threaded BLAS).
library(oligo) library(pd.huex.1.0.st.v2) library(oligoData) data(affyExonFS) res <- fitProbeLevelModel(affyExonFS) Background correcting... OK Normalizing... OK Summarizing... *** caught segfault *** address 0x7f93eacd3028, cause 'memory not mapped' Traceback: 1: .Call("R_sub_rcModelSummarize_plm", y, rowIndexList, PsiCode, PsiK, input.scale, PACKAGE = "preprocessCore") 2: theFun(y = transfo(mat), pnVec) 3: runSummarize(tmpMat, probeInfo$man_fsetid, method = method, verbose = verbose) 4: fitProbeLevelModel(affyExonFS) Possible actions: 1: abort (with core dump, if enabled) 2: normal R exit 3: exit R without saving workspace 4: exit R saving workspace Selection: << I selected '2'>> > sessionInfo() R version 3.4.1 Patched (2017-08-27 r73146) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Red Hat Enterprise Linux Matrix products: default BLAS/LAPACK: /opt/OpenBLAS/lib/libopenblas_haswellp-r0.2.20.so locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C [3] 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 [7] LC_PAPER=en_US.UTF-8 LC_NAME=C [9] LC_ADDRESS=C LC_TELEPHONE=C [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C attached base packages: [1] stats4 parallel stats graphics grDevices utils datasets [8] methods base other attached packages: [1] oligoData_1.8.0 pd.huex.1.0.st.v2_3.14.1 DBI_0.7 [4] RSQLite_2.0 oligo_1.40.2 Biostrings_2.44.2 [7] XVector_0.16.0 IRanges_2.10.2 S4Vectors_0.14.3 [10] Biobase_2.36.2 oligoClasses_1.38.0 BiocGenerics_0.22.0 loaded via a namespace (and not attached): [1] Rcpp_0.12.12 compiler_3.4.1 [3] BiocInstaller_1.26.0 GenomeInfoDb_1.12.2 [5] bitops_1.0-6 iterators_1.0.8 [7] tools_3.4.1 zlibbioc_1.22.0 [9] digest_0.6.12 bit_1.1-12 [11] memoise_1.1.0 tibble_1.3.4 [13] preprocessCore_1.38.1 lattice_0.20-35 [15] ff_2.2-13 rlang_0.1.2 [17] Matrix_1.2-11 foreach_1.4.3 [19] DelayedArray_0.2.7 GenomeInfoDbData_0.99.0 [21] affxparser_1.48.0 bit64_0.9-7 [23] grid_3.4.1 blob_1.1.0 [25] splines_3.4.1 codetools_0.2-15 [27] matrixStats_0.52.2 GenomicRanges_1.28.4 [29] SummarizedExperiment_1.6.3 RCurl_1.95-4.8 [31] affyio_1.46.0 >
Thanks James for your suggestion! But... no, reinstalling
oligoData
unfortunately did not solve it.RMA normalization just works fine?!?. See below.
As said before, could it be that
preprocessCore
somehow is not working with a multi-threaded BLAS? However, I am not knowledgeable enough to show this is the case....Ah, I missed that part. There is C code intended to work with parallel threads, but that's all beyond my ken. It's all Ben Bolstad's code, and he is long since gone, so I am afraid you are probably on your own.
The easiest fix would be to compile a version of R that uses the stock BLAS libraries.
It is debatable as to how far gone over the edge I am :) But it is true that my activity level has been minimal for some years now.
In any case preprocessCore does have and has long had it's own pthreads based multithreading implementation. You can control the number of threads it is using with a shell set R_THREADS variable (eg export R_THREADS=4) before starting R. I suspect that there is some sort of interaction between this and multi-threaded BLAS that might be solvable by putting a mutex or two in the right place. But that is just a wild guess.
Also it might be possible to turn threading off in OpenBLAS rather than just recompiling R. See
https://github.com/xianyi/OpenBLAS/wiki/faq#multi-threaded
Thanks Ben for replying so promptly! As per your suggestion (and for completeness I also post this here): I have opened an issue on GitHub: https://github.com/bmbolstad/preprocessCore/issues/1 to which I also added some more information on my attempts to get it working.