Can ChIPQC analyze mandarin duck ChIP-Seq data?
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Gary ▴ 20
@gary-7967
Last seen 2.4 years ago

Hi,

I am analyzing mandarin duck (Aix galericulata) ChIP-Seq data. We have a mandarin duck genome assembly .fa file and a genome annotation .gff file produced by our cooperators. May I know whether ChIPQC can analyze mandarin duck histone modification ChIP-Seq data? Could you show me how to do it, if it is doable? Many thanks.

Best,

Gary

ChIPQC • 671 views
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@thomas-carroll-7019
Last seen 13 months ago
United States/New York/The Rockefeller …

 

hi Gary,

ChIPQC should work fine for BAM files aligned to any genome. Since there isn't a prebuilt TxDB package for mandarin duck, the summary of gene signal within genic regions is not immediately supported.

To run ChIPQC on a single BAM.

ChIPQCsample("MyDuckData.bam")

I would recommend running all your samples together using the ChIPQC function with a sample sheet showing the set-up of your experiment. This is detailed in the package vignette (http://bioconductor.org/packages/release/bioc/vignettes/ChIPQC/inst/doc/ChIPQC.pdf)

You can also  provide custom annotation to ChIPQC in the form of a list of GRanges objects. This is described in this workshop

http://bioconductor.org/help/course-materials/2014/BioC2014/Bioc2014_ChIPQC_Practical.pdf

and in this previous post

creating custom genome annotation for the ChIPQC package

If you have a gtf for gene models you should be able to build a ChIPQC annotation for your genome of interest.

require(GenomicFeatures)
require(GenomicRanges)

txdb <- makeTxDbFromGFF("MyGTF.gtf",format="gtf") 

All5utrs <- reduce(unique(unlist(fiveUTRsByTranscript(txdb))))
All3utrs <- reduce(unique(unlist(threeUTRsByTranscript(txdb))))
Allcds <- reduce(unique(unlist(cdsBy(txdb,"tx"))))
Allintrons <- reduce(unique(unlist(intronsByTranscript(txdb))))
Alltranscripts <- reduce(unique(unlist(transcripts(txdb))))

posAllTranscripts <- Alltranscripts[strand(Alltranscripts) == "+"]
posAllTranscripts <- posAllTranscripts[!(start(posAllTranscripts)-20000 < 0)]
negAllTranscripts <- Alltranscripts[strand(Alltranscripts) == "-"]
chrLimits <- seqlengths(negAllTranscripts)[as.character(seqnames(negAllTranscripts))]      
negAllTranscripts <- negAllTranscripts[!(end(negAllTranscripts)+20000 > chrLimits)]      
Alltranscripts <- c(posAllTranscripts,negAllTranscripts)
Promoters500 <-  reduce(flank(Alltranscripts,500))    
Promoters2000to500 <-  reduce(flank(Promoters500,1500))
LongPromoter20000to2000  <- reduce(flank(Promoters2000to500,18000))

duckAnnotation <- list(version="",LongPromoter20000to2000=LongPromoter20000to2000,
            Promoters2000to500=Promoters2000to500,Promoters500=Promoters500,
            All5utrs=All5utrs,Alltranscripts=Alltranscripts,Allcds=Allcds,
            Allintrons=Allintrons,All3utrs=All3utrs)

ChIPQCsample("MyDuckData.bam",annotation=duckAnnotation)

 

very best,

tom

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