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
hi,
I think your post has been cut off here. Could you post the full design table?
Thank you,
tom
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
Maybe we see the table better outside a code chunk?
The design table:
SampleID Tissue Factor Condition Treatment Replicate bamReads ControlID bamControl Peaks PeakCallerSGA_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
Hi,
I am also trying to make the input and ChIP curves plot on the same graph. Did you figure this out?