I am running IHW in a GWAS setting and after 2 days of processing, I get the following error message:
libgomp: Thread creation failed: Resource temporarily unavailable
When I Google this error, it seems that it is coming somehow from Lsymphony which IHW calls. While I see an option in IHW that allows me to set a solver, I am wondering how to actually fix this error.
I might as well note here that if I try to set lp_solver="gurobi", I get the error message:
Error in gurobi(model, params) : could not find function "gurobi"
My session info is:
R version 3.4.3 Patched (2018-01-20 r74142) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Red Hat Enterprise Linux Server release 6.9 (Santiago) Matrix products: default BLAS: R/3.4.x/lib64/R/lib/libRblas.so LAPACK: R/3.4.x/lib64/R/lib/libRlapack.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] parallel stats4 stats graphics grDevices datasets utils [8] methods base other attached packages: [1] EBImage_4.20.1 bnbc_1.0.0 [3] lmerTest_2.0-36 lme4_1.1-15 [5] preprocessCore_1.40.0 BSgenome.Hsapiens.UCSC.hg19_1.4.0 [7] BSgenome_1.46.0 rtracklayer_1.38.3 [9] Biostrings_2.46.0 XVector_0.18.0 [11] IHW_1.6.0 Matrix_1.2-12 [13] readr_1.1.1 SummarizedExperiment_1.8.1 [15] DelayedArray_0.4.1 Biobase_2.38.0 [17] GenomicRanges_1.30.3 GenomeInfoDb_1.14.0 [19] IRanges_2.12.0 S4Vectors_0.16.0 [21] BiocGenerics_0.24.0 data.table_1.10.4-3 [23] matrixStats_0.53.1 scales_0.5.0 [25] tidyr_0.8.0 dplyr_0.7.4 [27] magrittr_1.5 qvalue_2.10.0 loaded via a namespace (and not attached): [1] nlme_3.1-131 bitops_1.0-6 bit64_0.9-7 [4] RColorBrewer_1.1-2 tools_3.4.3 backports_1.1.2 [7] R6_2.2.2 rpart_4.1-12 mgcv_1.8-22 [10] Hmisc_4.1-1 DBI_0.8 lazyeval_0.2.1 [13] colorspace_1.3-2 nnet_7.3-12 gridExtra_2.3 [16] bit_1.1-12 compiler_3.4.3 fdrtool_1.2.15 [19] htmlTable_1.11.2 slam_0.1-42 checkmate_1.8.5 [22] genefilter_1.60.0 tiff_0.1-5 stringr_1.3.0 [25] digest_0.6.15 Rsamtools_1.30.0 fftwtools_0.9-8 [28] foreign_0.8-69 minqa_1.2.4 jpeg_0.1-8 [31] base64enc_0.1-3 pkgconfig_2.0.1 htmltools_0.3.6 [34] lpsymphony_1.7.1 limma_3.34.9 htmlwidgets_1.0 [37] rlang_0.2.0 RSQLite_2.0 rstudioapi_0.7 [40] bindr_0.1 BiocParallel_1.12.0 acepack_1.4.1 [43] RCurl_1.95-4.10 GenomeInfoDbData_1.0.0 Formula_1.2-2 [46] Rcpp_0.12.15 munsell_0.4.3 abind_1.4-5 [49] stringi_1.1.6 MASS_7.3-48 zlibbioc_1.24.0 [52] plyr_1.8.4 blob_1.1.0 grid_3.4.3 [55] lattice_0.20-35 splines_3.4.3 annotate_1.56.1 [58] hms_0.4.1 locfit_1.5-9.1 knitr_1.20 [61] pillar_1.2.1 reshape2_1.4.3 XML_3.98-1.10 [64] glue_1.2.0 latticeExtra_0.6-28 png_0.1-7 [67] nloptr_1.0.4 gtable_0.2.0 purrr_0.2.4 [70] assertthat_0.2.0 ggplot2_2.2.1 xtable_1.8-2 [73] survival_2.41-3 tibble_1.4.2 memoise_1.1.0 [76] GenomicAlignments_1.14.1 AnnotationDbi_1.40.0 bindrcpp_0.2 [79] cluster_2.0.6 sva_3.26.0
We have been using the package successfully quite a few times, so I don't think it is a basic issue. It could depend on this exact set of p-values. I think we have a LOT of p-values for this application, but I will let Kipper speak to the details here.