CHIPQC error regarding BiocParallel
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bioinfouser2 ▴ 10
@bioinfouser2-15147
Last seen 9 months ago

Hello,

I am trying to run ChIPQC on 83 samples. I am using the following line to make the DBA object:

CHIPQC_DBA = ChIPQC(samples,consensus = TRUE, bCount=TRUE, summits=250, annotation="hg38", blacklist = blacklist.hg38)

It is running until this point and crashing with the following error:

Checking chromosomes:
[1] "chr1"
Compiling annotation...
Adding controls...
Counting reads in consensus peakset...
Re-centering peaks...
Computing metrics for 83 samples...
'BiocParallel' did not register default BiocParallelParam:
  comparison of these types is not implemented
Error in if (!bpschedule(BPPARAM) || length(X) == 1L || bpnworkers(BPPARAM) ==  :
  missing value where TRUE/FALSE needed
Calls: ChIPQC -> bplapply -> bplapply -> bplapply -> bplapply
Execution halted

I would really appreciate if Rory or Thomas could help me on thise!

Here is my session info:

 R version 3.6.1 (2019-07-05)
Platform: x86_64-conda_cos6-linux-gnu (64-bit)
Running under: Ubuntu 16.04.6 LTS

Matrix products: default
BLAS/LAPACK: /fshare/users/sakibs/miniconda3/envs/latest_R_3.6/lib/R/lib/libRblas.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 utils     datasets
[8] methods   base

other attached packages:
 [1] TxDb.Hsapiens.UCSC.hg38.knownGene_3.10.0
 [2] GenomicFeatures_1.38.2
 [3] AnnotationDbi_1.48.0
 [4] ChIPQC_1.22.0
 [5] DiffBind_2.14.0
 [6] SummarizedExperiment_1.16.1
 [7] DelayedArray_0.12.3
 [8] BiocParallel_1.20.1
 [9] matrixStats_0.56.0
[10] Biobase_2.46.0
[11] GenomicRanges_1.38.0
[12] GenomeInfoDb_1.22.1
[13] IRanges_2.20.2
[14] S4Vectors_0.24.4
[15] BiocGenerics_0.32.0
[16] ggplot2_3.3.0

loaded via a namespace (and not attached):
  [1] amap_0.8-18
  [2] colorspace_1.4-1
  [3] rjson_0.2.20
  [4] hwriter_1.3.2
  [5] ellipsis_0.3.0
  [6] XVector_0.26.0
  [7] ggrepel_0.8.2
  [8] bit64_0.9-7
  [9] fansi_0.4.1
 [10] splines_3.6.1
 [11] TxDb.Rnorvegicus.UCSC.rn4.ensGene_3.2.2
 [12] Nozzle.R1_1.1-1
 [13] Rsamtools_2.2.3
 [14] annotate_1.64.0
 [15] GO.db_3.10.0
 [16] dbplyr_1.4.3
 [17] png_0.1-7
 [18] pheatmap_1.0.12
 [19] graph_1.64.0
 [20] TxDb.Hsapiens.UCSC.hg18.knownGene_3.2.2
 [21] compiler_3.6.1
 [22] httr_1.4.1
 [23] GOstats_2.52.0
 [24] backports_1.1.6
 [25] assertthat_0.2.1
 [26] Matrix_1.2-18
 [27] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
 [28] limma_3.42.2
 [29] cli_2.0.2
 [30] prettyunits_1.1.1
 [31] tools_3.6.1
 [32] gtable_0.3.0
 [33] glue_1.4.0
 [34] GenomeInfoDbData_1.2.2
 [35] Category_2.52.1
 [36] reshape2_1.4.4
 [37] systemPipeR_1.20.0
 [38] dplyr_0.8.5
 [39] batchtools_0.9.13
 [40] rappdirs_0.3.1
 [41] ShortRead_1.44.3
 [42] Rcpp_1.0.4.6
 [43] TxDb.Dmelanogaster.UCSC.dm3.ensGene_3.2.2
 [44] TxDb.Mmusculus.UCSC.mm9.knownGene_3.2.2
 [45] vctrs_0.2.4
 [46] Biostrings_2.54.0
 [47] gdata_2.18.0
 [48] rtracklayer_1.46.0
 [49] TxDb.Mmusculus.UCSC.mm10.knownGene_3.10.0
 [50] stringr_1.4.0
 [51] lifecycle_0.2.0
 [52] gtools_3.8.2
 [53] XML_3.99-0.3
 [54] edgeR_3.28.1
 [55] zlibbioc_1.32.0
 [56] scales_1.1.0
 [57] BSgenome_1.54.0
 [58] VariantAnnotation_1.32.0
 [59] hms_0.5.3
 [60] RBGL_1.62.1
 [61] RColorBrewer_1.1-2
 [62] yaml_2.2.1
 [63] curl_4.3
 [64] memoise_1.1.0
 [65] biomaRt_2.42.1
 [66] latticeExtra_0.6-29
 [67] stringi_1.4.6
 [68] RSQLite_2.2.0
 [69] genefilter_1.68.0
 [70] checkmate_2.0.0
 [71] caTools_1.18.0
 [72] chipseq_1.36.0
 [73] rlang_0.4.5
 [74] pkgconfig_2.0.3
 [75] bitops_1.0-6
 [76] TxDb.Celegans.UCSC.ce6.ensGene_3.2.2
 [77] lattice_0.20-41
 [78] purrr_0.3.4
 [79] GenomicAlignments_1.22.1
 [80] bit_1.1-15.2
 [81] tidyselect_1.0.0
 [82] GSEABase_1.48.0
 [83] AnnotationForge_1.28.0
 [84] plyr_1.8.6
 [85] magrittr_1.5
 [86] R6_2.4.1
 [87] gplots_3.0.3
 [88] base64url_1.4
 [89] DBI_1.1.0
 [90] pillar_1.4.3
 [91] withr_2.1.2
 [92] survival_3.1-12
 [93] RCurl_1.98-1.2
 [94] tibble_3.0.0
 [95] crayon_1.3.4
 [96] KernSmooth_2.23-16
 [97] BiocFileCache_1.10.2
 [98] jpeg_0.1-8.1
 [99] progress_1.2.2
[100] locfit_1.5-9.4
[101] grid_3.6.1
[102] data.table_1.12.8
[103] blob_1.2.1
[104] Rgraphviz_2.30.0
[105] digest_0.6.25
[106] xtable_1.8-4
[107] brew_1.0-6
[108] openssl_1.4.1
[109] munsell_0.5.0
[110] askpass_1.1`
CHIPQC Diffbind chipseq rory stark Thomas Carroll • 202 views
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Also, this R environment I was using with conda in our linux cluster, with R version 3.6, where I could successfully install ChIPQC. But in our linux cluster, R 3.4.1 is installed and when I tried to install it there, it shows the following error:

` * caught segfault * address (nil), cause 'memory not mapped' An irrecoverable exception occurred. R is aborting now ... Segmentation fault (core dumped) ERROR: loading failed * removing ‘/fshare/users/sakibs/R/x86_64-pc-linux-gnu-library/3.4/ChIPQC’

* caught segfault * address (nil), cause 'memory not mapped'

Traceback: 1: q("no", status = status, runLast = FALSE) 2: doexit(status = status) 3: doexitonerror() 4: errmsg("loading failed") 5: doinstallsource(pkgname, instdir, pkg, desc) 6: doinstall(pkg) 7: tools:::.install_packages() An irrecoverable exception occurred. R is aborting now ... Segmentation fault (core dumped)`

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