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Hi,
I am trying to run ChIPQC on my data but for my final report I get blank plots for CrossCoverage and the Signal profile. I don't get any errors when creating the Chip object nor do I get errors when generating the report so it's hard to troubleshoot.
Here is a link to my report using only chr12 (I get the same for the full dataset) : http://tinyurl.com/chipqc-report
I have below my sample table:
SampleID Factor Replicate bamReads ControlID
1 Nanog-Rep1 Nanog X1 chr12-bam/H1hesc_Nanog_Rep1_chr12_aln.bam Nanog-Input1
2 Nanog-Rep2 Nanog X2 chr12-bam/H1hesc_Nanog_Rep2_chr12_aln.bam Nanog-Input2
3 Pou5f1-Rep1 Pou5f1 X1 chr12-bam/H1hesc_Pou5f1_Rep1_chr12_aln.bam Pou5f1-Input1
4 Pou5f1-Rep2 Pou5f1 X2 chr12-bam/H1hesc_Pou5f1_Rep2_chr12_aln.bam Pou5f1-Input2
bamControl Peaks PeakCaller
1 chr12-bam/H1hesc_Input_Rep1_chr12_aln.bam chr12-bed/Nanog-rep1_peaks.narrowPeak narrow
2 chr12-bam/H1hesc_Input_Rep2_chr12_aln.bam chr12-bed/Nanog-rep2_peaks.narrowPeak narrow
3 chr12-bam/H1hesc_Input_Rep1_chr12_aln.bam chr12-bed/Pou5f1-rep1_peaks.narrowPeak narrow
4 chr12-bam/H1hesc_Input_Rep2_chr12_aln.bam chr12-bed/Pou5f1-rep2_peaks.narrowPeak narrow
I also have the code I ran, including the sessionInfo():
samples <- read.csv('samplesheet_chr12.csv') chipObj <- ChIPQC(samples, annotation="hg19") ChIPQCreport(chipObj, reportName="ChIP QC report: Nanog and Pou5f1", reportFolder="ChIPQCreport", facet=FALSE) sessionInfo() R version 3.3.3 (2017-03-06) Platform: x86_64-apple-darwin13.4.0 (64-bit) Running under: OS X Yosemite 10.10.5 locale: [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8 attached base packages: [1] parallel stats4 stats graphics grDevices utils datasets methods base other attached packages: [1] ChIPQC_1.10.3 DiffBind_2.2.12 SummarizedExperiment_1.4.0 [4] Biobase_2.34.0 GenomicRanges_1.26.4 GenomeInfoDb_1.10.3 [7] IRanges_2.8.2 S4Vectors_0.12.2 BiocGenerics_0.20.0 [10] ggplot2_2.2.1 loaded via a namespace (and not attached): [1] Category_2.40.0 bitops_1.0-6 [3] RColorBrewer_1.1-2 TxDb.Hsapiens.UCSC.hg18.knownGene_3.2.2 [5] UpSetR_1.3.3 backports_1.1.0 [7] tools_3.3.3 R6_2.2.1 [9] KernSmooth_2.23-15 DBI_0.6-1 [11] lazyeval_0.2.0 colorspace_1.3-2 [13] gridExtra_2.2.1 TxDb.Celegans.UCSC.ce6.ensGene_3.2.2 [15] Nozzle.R1_1.1-1 sendmailR_1.2-1 [17] graph_1.52.0 TxDb.Mmusculus.UCSC.mm10.knownGene_3.4.0 [19] labeling_0.3 rtracklayer_1.34.2 [21] checkmate_1.8.2 caTools_1.17.1 [23] scales_0.4.1 ChIPseeker_1.10.3 [25] BatchJobs_1.6 genefilter_1.56.0 [27] RBGL_1.50.0 stringr_1.2.0 [29] digest_0.6.12 Rsamtools_1.26.2 [31] DOSE_3.0.10 AnnotationForge_1.16.1 [33] XVector_0.14.1 base64enc_0.1-3 [35] plotrix_3.6-5 limma_3.30.13 [37] rlang_0.1.1 RSQLite_1.1-2 [39] BBmisc_1.11 TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2 [41] GOstats_2.40.0 hwriter_1.3.2 [43] BiocParallel_1.8.2 gtools_3.5.0 [45] GOSemSim_2.0.4 dplyr_0.5.0 [47] RCurl_1.95-4.8 magrittr_1.5 [49] GO.db_3.4.0 Matrix_1.2-10 [51] Rcpp_0.12.11 munsell_0.4.3 [53] stringi_1.1.5 edgeR_3.16.5 [55] zlibbioc_1.20.0 fail_1.3 [57] gplots_3.0.1 plyr_1.8.4 [59] qvalue_2.6.0 grid_3.3.3 [61] gdata_2.17.0 DO.db_2.9 [63] lattice_0.20-35 Biostrings_2.42.1 [65] splines_3.3.3 GenomicFeatures_1.26.4 [67] annotate_1.52.1 locfit_1.5-9.1 [69] knitr_1.16 fgsea_1.0.2 [71] igraph_1.0.1 boot_1.3-19 [73] rjson_0.2.15 systemPipeR_1.8.1 [75] reshape2_1.4.2 biomaRt_2.30.0 [77] fastmatch_1.1-0 XML_3.98-1.7 [79] ShortRead_1.32.1 latticeExtra_0.6-28 [81] data.table_1.10.4 gtable_0.2.0 [83] amap_0.8-14 assertthat_0.2.0 [85] chipseq_1.24.0 gridBase_0.4-7 [87] TxDb.Mmusculus.UCSC.mm9.knownGene_3.2.2 TxDb.Rnorvegicus.UCSC.rn4.ensGene_3.2.2 [89] xtable_1.8-2 survival_2.41-3 [91] TxDb.Hsapiens.UCSC.hg38.knownGene_3.4.0 pheatmap_1.0.8 [93] tibble_1.3.1 GenomicAlignments_1.10.1 [95] AnnotationDbi_1.36.2 memoise_1.1.0 [97] brew_1.0-6 TxDb.Dmelanogaster.UCSC.dm3.ensGene_3.2.2 [99] GSEABase_1.36.0
Any help on this would be great and much appreciated.
Thanks!
Meeta
Hi Tom,
Adding the Tissue and Condition columns appears to have solved the problem. Thanks very much!
Best,
Meeta