ChIPQC plotCoverageHist() and plotCC() not showing inputs
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atisou • 0
@atisou-7468
Last seen 4.4 years ago
Switzerland

Hi,

I have a ChIP-seq experimental design  consisting of 2 different conditions, with 3 biological replicates for each, thus N=6 different ChIP samples and with N=6 inputs samples (total N=12 samples).

The design table:

SampleID    Tissue    Factor    Condition    Treatment    Replicate    bamReads    ControlID    bamControl    Peaks    PeakCaller
SGA_1    cord    E2F1    SGA    E2F1    SGA_1.bam input_SGA_1    SGA_input_1.bam    SGA_1_macs_peaks.xls    macs
SGA_2    cord    E2F1    SGA    E2F1    SGA_2.bam input_SGA_2    SGA_input_2.bam    SGA_2_macs_peaks.xls    macs
SGA_3    cord    E2F1    SGA    E2F1    SGA_3.bam input_SGA_3    SGA_input_3.bam    SGA_3_macs_peaks.xls    macs
AGA_1    cord    E2F1    AGA    E2F1    AGA_1.bam input_AGA_1    AGA_input_1.bam    AGA_1_macs_peaks.xls    macs
AGA_2    cord    E2F1    AGA    E2F1    AGA_2.bam input_AGA_2    AGA_input_2.bam    AGA_2_macs_peaks.xls    macs
AGA_3    cord    E2F1    AGA    E2F1    AGA_3.bam input_AGA_3    AGA_input_3.bam    AGA_3_macs_peaks.xls    macs

The commands I ran:

res <- ChIPQC(experiment = my_design_df, chromosomes = "1")

plotCoverageHist(object = res, facetBy = "Condition")

plotCC(object = res, facetBy = "Condition")

My questions are:

1. how to include the control inputs data with plotCoverageHist() and plotCC() ?

2.  how are the QC metrics computed for the control inputs in the ChIPQC object in the absence of input peaks files?

Thanks in advance for your help,

Hatice

University of Fribourg

 

R version 3.3.2 (2016-10-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 14.04.5 LTS

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               LC_TIME=de_CH.UTF-8        LC_COLLATE=en_US.UTF-8     LC_MONETARY=de_CH.UTF-8   
 [6] LC_MESSAGES=en_US.UTF-8    LC_PAPER=de_CH.UTF-8       LC_NAME=C                  LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=de_CH.UTF-8 LC_IDENTIFICATION=C       

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

other attached packages:
 [1] ChIPQC_1.8.9               DiffBind_2.0.9             SummarizedExperiment_1.2.3 Biobase_2.32.0             GenomicRanges_1.24.3      
 [6] GenomeInfoDb_1.8.7         IRanges_2.6.1              S4Vectors_0.10.3           BiocGenerics_0.18.0        ggplot2_2.2.1             

 

 

 

ChIPQC plotCoverageHist plotCC input • 723 views
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hi,

 

I think your post has been cut off here. Could you post the full design table?

 

Thank you,

 

tom

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Dear Thomas,

Thanks for your reply.

To achieve the input versus IP profile plots (CC and CoverageHist), I have to tweak around the design_table (separate comment posted previously) by adding the control samples as extra samples, in order to have the input samples to be taken into account:

SampleID Tissue Factor Condition Treatment Replicate bamReads ControlID bamControl Peaks PeakCaller
E2F1_SGA_1 cord E2F1 SGA E2F1 1 E2F1_SGA_1.bam input_SGA_1 input_SGA_1.bam E2F1_SGA_1_macs_peaks.xls.xls macs
E2F1_SGA_2 cord E2F1 SGA E2F1 2 E2F1_SGA_2.bam input_SGA_2 input_SGA_2.bam E2F1_SGA_2_macs_peaks.xls.xls macs
E2F1_SGA_3 cord E2F1 SGA E2F1 3 E2F1_SGA_3.bam input_SGA_3 input_SGA_3.bam E2F1_SGA_3_macs_peaks.xls.xls macs
E2F1_AGA_1 cord E2F1 AGA E2F1 1 E2F1_AGA_1.bam input_AGA_1 input_AGA_1.bam E2F1_AGA_1_macs_peaks.xls.xls macs
E2F1_AGA_2 cord E2F1 AGA E2F1 2 E2F1_AGA_2.bam input_AGA_2 input_AGA_2.bam E2F1_AGA_2_macs_peaks.xls.xls macs
E2F1_AGA_3 cord E2F1 AGA E2F1 3 E2F1_AGA_3.bam input_AGA_3 input_AGA_3.bam E2F1_AGA_3_macs_peaks.xls.xls macs
input_SGA_1 cord Control SGA Control 1 input_SGA_1.bam input_SGA_1 input_SGA_1.bam E2F1_SGA_1_macs_peaks.xls.xls macs
input_SGA_2 cord Control SGA Control 2 input_SGA_2.bam input_SGA_2 input_SGA_2.bam E2F1_SGA_2_macs_peaks.xls.xls macs
input_SGA_3 cord Control SGA Control 3 input_SGA_3.bam input_SGA_3 input_SGA_3.bam E2F1_SGA_3_macs_peaks.xls.xls macs
input_AGA_1 cord Control AGA Control 1 input_AGA_1.bam input_AGA_1 input_AGA_1.bam E2F1_AGA_1_macs_peaks.xls.xls macs
input_AGA_2 cord Control AGA Control 2 input_AGA_2.bam input_AGA_2 input_AGA_2.bam E2F1_AGA_2_macs_peaks.xls.xls macs
input_AGA_3 cord Control AGA Control 3 input_AGA_3.bam input_AGA_3 input_AGA_3.bam E2F1_AGA_3_macs_peaks.xls.xls macs

 

So, basically this works like that, but this is not what the vignette shows, i.e input and IP curves on same plots.

Cheers,

 

ps: I can send you the exact code and plots by email if you want

 

 

 

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Maybe we see the table better outside a code chunk?

The design table:

SampleID    Tissue    Factor    Condition    Treatment    Replicate    bamReads    ControlID    bamControl    Peaks    PeakCaller
SGA_1    cord    E2F1    SGA    E2F1  1  SGA_1.bam input_SGA_1    SGA_input_1.bam    SGA_1_macs_peaks.xls    macs
SGA_2    cord    E2F1    SGA    E2F1  2  SGA_2.bam input_SGA_2    SGA_input_2.bam    SGA_2_macs_peaks.xls    macs
SGA_3    cord    E2F1    SGA    E2F1  3  SGA_3.bam input_SGA_3    SGA_input_3.bam    SGA_3_macs_peaks.xls    macs
AGA_1    cord    E2F1    AGA    E2F1  1  AGA_1.bam input_AGA_1    AGA_input_1.bam    AGA_1_macs_peaks.xls    macs
AGA_2    cord    E2F1    AGA    E2F1  2  AGA_2.bam input_AGA_2    AGA_input_2.bam    AGA_2_macs_peaks.xls    macs
AGA_3    cord    E2F1    AGA    E2F1  3  AGA_3.bam input_AGA_3    AGA_input_3.bam    AGA_3_macs_peaks.xls    macs

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Hi,

I am also trying to make the input and ChIP curves plot on the same graph. Did you figure this out? 

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