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`
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)`