Taking a closer look at peaks

ChIP-seq with Bioconductor in R

Peter Humburg

Statistician, Macquarie University

Using Gviz

What are we plotting?

Setting-up coordinates

library(Gviz)

ideogram <- IdeogramTrack("chr12", 
                          "hg19")

axis <- GenomeAxisTrack()

plotTracks(list(ideogram, axis), 
           from=101360000, 
           to=101380000)

Adding Data

cover_track <- DataTrack(cover_ranges,window=100000,type='h',name="Coverage")
plotTracks(list(ideogram, cover_track, axis), from=101360000, to=101380000)

Adding Annotations

peak_track <- AnnotationTrack(peaks, name="Peaks")
plotTracks(list(ideogram, cover_track, peak_track, axis), 
           from=101360000, to=101380000)

Gene Annotations

library(TxDb.Hsapiens.UCSC.hg19.knownGene)

tx <- GeneRegionTrack(TxDb.Hsapiens.UCSC.hg19.knownGene, chromosome="chr12", 
                      start=101360000, end=101380000, name="Genes")
plotTracks(list(ideogram, cover_track, peak_track, tx, axis),
           from=101360000, to=101380000)

Let's practice!

ChIP-seq with Bioconductor in R