Hi,

I am running bumphunter in an ubuntu server (443 G of RAM and 75 G of swap) on data from approx. 2000 EPIC arrays. This is the error I am getting when trying to run it with multicore: "Error in nulltabs[[i]] : subscript out of bounds". When running it with a single core, this error is not happening (but the process lasts two weeks, so this is not a solution).

This is my command line:

registerDoParallel( cores = 3)

res <- bumphunter(M.combat, design, coeff=2, chr= manifestInfo$chr, pos=manifestInfo$pos, maxGap=300, B=2000, cutoff=NULL, pickCutoff=TRUE, pickCutoffQ=0.995,nullMethod="bootstrap",verbose=TRUE)

[bumphunterEngine] Parallelizing using 3 workers/cores (backend: doParallelMC, version: 1.0.10).
[bumphunterEngine] Computing coefficients.
[bumphunterEngine] Performing 2000 bootstraps.
[bumphunterEngine] Computing marginal bootstrap p-values.
[bumphunterEngine] cutoff: 0.085
[bumphunterEngine] Finding regions.
[bumphunterEngine] Found 11510 bumps.
[bumphunterEngine] Computing regions for each bootstrap.
[bumphunterEngine] Estimating p-values and FWER.
Error in nulltabs[[i]] : subscript out of bounds

This is my session info:

R version 3.4.4 (2018-03-15)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.4 LTS

Matrix products: default
BLAS: /usr/lib/libblas/libblas.so.3.6.0
LAPACK: /usr/lib/lapack/liblapack.so.3.6.0

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C
 [3] LC_TIME=es_ES.UTF-8        LC_COLLATE=en_US.UTF-8
 [5] LC_MONETARY=es_ES.UTF-8    LC_MESSAGES=en_US.UTF-8
 [7] LC_PAPER=es_ES.UTF-8       LC_NAME=C
 [9] LC_ADDRESS=C               LC_TELEPHONE=C
[11] LC_MEASUREMENT=es_ES.UTF-8 LC_IDENTIFICATION=C

attached base packages:
 [1] parallel  stats4    grid      stats     graphics  grDevices utils
 [8] datasets  methods   base

other attached packages:
 [1] bumphunter_1.20.0    locfit_1.5-9.1       iterators_1.0.9
 [4] foreach_1.4.4        GenomicRanges_1.30.3 GenomeInfoDb_1.14.0
 [7] IRanges_2.12.0       S4Vectors_0.16.0     BiocGenerics_0.24.0
[10] readstata13_0.9.0    readr_1.1.1          survey_3.33-2
[13] Matrix_1.2-12        foreign_0.8-70       Hmisc_4.1-1
[16] ggplot2_2.2.1        Formula_1.2-2        lattice_0.20-35
[19] survival_2.42-3

loaded via a namespace (and not attached):
 [1] httr_1.3.1                 Biobase_2.38.0
 [3] RMySQL_0.10.14             bit64_0.9-7
 [5] splines_3.4.4              assertthat_0.2.0
 [7] latticeExtra_0.6-28        doRNG_1.6.6
 [9] blob_1.1.1                 Rsamtools_1.30.0
[11] GenomeInfoDbData_1.0.0     progress_1.1.2
[13] pillar_1.2.2               RSQLite_2.1.0
[15] backports_1.1.2            digest_0.6.15
[17] RColorBrewer_1.1-2         XVector_0.18.0
[19] checkmate_1.8.5            colorspace_1.3-2
[21] htmltools_0.3.6            plyr_1.8.4
[23] XML_3.98-1.11              pkgconfig_2.0.1
[25] biomaRt_2.34.2             zlibbioc_1.24.0
[27] xtable_1.8-2               scales_0.5.0
[29] BiocParallel_1.12.0        htmlTable_1.11.2
[31] tibble_1.4.2               pkgmaker_0.22
[33] SummarizedExperiment_1.8.1 GenomicFeatures_1.30.3
[35] nnet_7.3-12                lazyeval_0.2.1
[37] magrittr_1.5               memoise_1.1.0
[39] prettyunits_1.0.2          tools_3.4.4
[41] registry_0.5               data.table_1.10.4-3
[43] hms_0.4.2                  matrixStats_0.53.1
[45] stringr_1.3.0              munsell_0.4.3
[47] cluster_2.0.6              rngtools_1.2.4
[49] DelayedArray_0.4.1         AnnotationDbi_1.40.0
[51] Biostrings_2.46.0          compiler_3.4.4
[53] rlang_0.2.0                RCurl_1.95-4.10
[55] rstudioapi_0.7             htmlwidgets_1.2
[57] bitops_1.0-6               base64enc_0.1-3
[59] gtable_0.2.0               codetools_0.2-15
[61] DBI_0.8                    R6_2.2.2
[63] GenomicAlignments_1.14.2   gridExtra_2.3
[65] rtracklayer_1.38.3         knitr_1.20
[67] bit_1.1-12                 stringi_1.1.7
[69] Rcpp_0.12.16               rpart_4.1-13
[71] acepack_1.4.1

Thanks!