Question: ChIPQC report missing figures
0
gravatar for meeta.mistry
2.4 years ago by
meeta.mistry20
United States
meeta.mistry20 wrote:

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

 

chipqc software error • 420 views
ADD COMMENTlink modified 2.4 years ago by Thomas Carroll400 • written 2.4 years ago by meeta.mistry20
Answer: ChIPQC report missing figures
1
gravatar for Thomas Carroll
2.4 years ago by
United States/New York/The Rockefeller University
Thomas Carroll400 wrote:
hi Meeta, Could you try providing ChIPQC with a full samplesheet including the columns Tissue and Condition (These can be filled with NA) and replace the replicate with 1 and 2 instead of X1 and X? This may fix the missing plots. If you are still having problems with this then please send me the ChIPQC object (to tc.infomatics@gmail.com) used to generate the report and i will look from there. thank you, tom On Sun, Jun 11, 2017 at 5:26 PM, meeta.mistry [bioc] < noreply@bioconductor.org> wrote: > Activity on a post you are following on support.bioconductor.org > > User meeta.mistry <https: support.bioconductor.org="" u="" 7355=""/> wrote Question: > ChIPQC report missing figures <https: support.bioconductor.org="" p="" 96933=""/>: > > > 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 > <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 > > > > ------------------------------ > > Post tags: chipqc, software error > > You may reply via email or visit ChIPQC report missing figures >
ADD COMMENTlink written 2.4 years ago by Thomas Carroll400

Hi Tom,

Adding the Tissue and Condition columns appears to have solved the problem. Thanks very much!

Best,

Meeta

ADD REPLYlink written 2.4 years ago by meeta.mistry20
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