ChIPQC makes a neverending loop while using all chromosomes
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@lauramannarino-21878
Last seen 3.1 years ago
Milan

While running ChIPQC on all chromosomes it seems to enter a loop, since it finishes the computation on chromosome Y and begins again from chromosome 1. This does not happen with only one chromosome.

My sessionInfo here:

R version 3.6.1 (2019-07-05)
Platform: x86_64-suse-linux-gnu (64-bit)
Running under: openSUSE Tumbleweed

Matrix products: default
BLAS: /usr/lib64/R/lib/libRblas.so
LAPACK: /usr/lib64/R/lib/libRlapack.so

Random number generation:
RNG: Mersenne-Twister
Normal: Inversion
Sample: Rounding

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

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

other attached packages:
[1] ChIPQC_1.21.0 DiffBind_2.12.0
[3] SummarizedExperiment_1.14.0 DelayedArray_0.10.0
[5] BiocParallel_1.18.1 matrixStats_0.54.0
[7] Biobase_2.44.0 GenomicRanges_1.36.0
[9] GenomeInfoDb_1.20.0 IRanges_2.18.0
[11] S4Vectors_0.22.0 BiocGenerics_0.30.0
[13] ggplot2_3.2.0

loaded via a namespace (and not attached):
[1] amap_0.8-17
[2] colorspace_1.4-1
[3] rjson_0.2.20
[4] hwriter_1.3.2
[5] htmlTable_1.13.1
[6] XVector_0.24.0
[7] base64enc_0.1-4
[8] rstudioapi_0.8 [9] ggrepel_0.8.1
[10] bit64_0.9-7
[11] AnnotationDbi_1.46.0
[12] splines_3.6.1
[13] TxDb.Rnorvegicus.UCSC.rn4.ensGene_3.2.2
[14] geneplotter_1.62.0
[15] knitr_1.20
[16] Nozzle.R1_1.1-1
[17] Formula_1.2-3
[18] Rsamtools_2.0.0
[19] annotate_1.62.0
[20] cluster_2.1.0
[21] GO.db_3.8.2
[22] pheatmap_1.0.12
[23] graph_1.62.0
[24] TxDb.Hsapiens.UCSC.hg18.knownGene_3.2.2
[25] compiler_3.6.1
[26] httr_1.4.0
[27] GOstats_2.50.0
[28] backports_1.1.4
[29] assertthat_0.2.1
[30] Matrix_1.2-17
[31] lazyeval_0.2.1
[32] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
[33] limma_3.40.2
[34] acepack_1.4.1
[35] htmltools_0.3.6
[36] prettyunits_1.0.2
[37] tools_3.6.1
[38] gtable_0.3.0
[39] glue_1.3.1
[40] GenomeInfoDbData_1.2.1
[41] Category_2.50.0
[42] reshape2_1.4.3
[43] systemPipeR_1.18.0
[44] dplyr_0.8.3
[45] batchtools_0.9.11
[46] rappdirs_0.3.1
[47] ShortRead_1.42.0
[48] Rcpp_1.0.1
[49] TxDb.Dmelanogaster.UCSC.dm3.ensGene_3.2.2
[50] TxDb.Mmusculus.UCSC.mm9.knownGene_3.2.2
[51] Biostrings_2.52.0
[52] gdata_2.18.0
[53] rtracklayer_1.44.0
[54] TxDb.Mmusculus.UCSC.mm10.knownGene_3.4.7
[55] stringr_1.4.0
[56] gtools_3.8.1
[57] XML_3.98-1.19
[58] edgeR_3.26.3
[59] zlibbioc_1.30.0
[60] scales_1.0.0
[61] BSgenome_1.52.0
[62] VariantAnnotation_1.30.1
[63] hms_0.4.2
[64] RBGL_1.60.0
[65] RColorBrewer_1.1-2
[66] yaml_2.2.0
[67] memoise_1.1.0
[68] gridExtra_2.3
[69] biomaRt_2.40.0
[70] rpart_4.1-15
[71] latticeExtra_0.6-28
[72] stringi_1.2.4
[73] RSQLite_2.1.1
[74] genefilter_1.66.0
[75] checkmate_1.9.3
[76] GenomicFeatures_1.36.1
[77] caTools_1.17.1
[78] chipseq_1.34.0
[79] rlang_0.4.0
[80] pkgconfig_2.0.2
[81] bitops_1.0-6
[82] TxDb.Celegans.UCSC.ce6.ensGene_3.2.2
[83] lattice_0.20-38
[84] purrr_0.3.0
[85] GenomicAlignments_1.20.0
[86] htmlwidgets_1.3
[87] bit_1.1-14
[88] tidyselect_0.2.5
[89] GSEABase_1.46.0
[90] AnnotationForge_1.26.0
[91] plyr_1.8.4
[92] magrittr_1.5
[93] DESeq2_1.24.0
[94] R6_2.4.0
[95] gplots_3.0.1.1
[96] Hmisc_4.2-0
[97] base64url_1.4
[98] DBI_1.0.0
[99] pillar_1.3.1
[100] foreign_0.8-71
[101] withr_2.1.2
[102] survival_2.44-1.1
[103] RCurl_1.95-4.11
[104] nnet_7.3-12
[105] tibble_2.1.3
[106] crayon_1.3.4
[107] KernSmooth_2.23-15
[108] progress_1.2.2
[109] locfit_1.5-9.1
[110] grid_3.6.1
[111] data.table_1.12.2
[112] blob_1.1.1
[113] Rgraphviz_2.28.0
[114] digest_0.6.18
[115] xtable_1.8-3
[116] brew_1.0-6
[117] munsell_0.5.0enter code here
chipqc chipseq ChIPQC • 850 views
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