Chapter 3 Parse getTagMatrix

Function getTagMatrix is different from normalizeToMatrix which is used to use target genomic regions to do enrichment analysis around specific regions. While normalizeToMatrix is using binding signals on genome in bigwig files and do the enrichment analysis on specific regions.

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3.1 Do enrichment analysis

library(ChIPseeker)
library(TxDb.Hsapiens.UCSC.hg19.knownGene)
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene

files <- getSampleFiles()

seek_list <- lapply(4:5, function(x){
  peak <- readPeakFile(files[[x]])
  
  ## The results of binning method and normal method are nearly the same. 
  tagMatrix_binning <- getTagMatrix(peak = peak, TxDb = txdb, 
                                    upstream = 3000, downstream = 3000, 
                                    type = "body", by = "gene", 
                                    nbin = 800)
})

# >> binning method is used...2023-10-17 21:06:24
# >> preparing body regions by gene... 2023-10-17 21:06:24
# >> preparing tag matrix by binning...  2023-10-17 21:06:24 
# ...

mat_df <- retriveData(mat.list = seek_list,
                      sample.names = c("CBX6","CBX7"),
                      ChIPseeker = T)

3.2 Profile plot

ChipVis(object = mat_df,plot.type = "profile")

We can use ChipSeeker to see the original plot:

plotPeakProf2(files[4:5], 
              upstream = rel(0.2), downstream = rel(0.2),
              by = "gene", type = "body",
              TxDb = txdb, facet = "column", 
              nbin = 800,free_y = FALSE)

3.3 Heatmap plot

ChipVis(object = mat_df,plot.type = "heatmap")

Merge facet panels:

ChipVis(object = mat_df,plot.type = "heatmap",
        merge_facet = T)

Assign multiple color scales:

ChipVis(object = mat_df,plot.type = "heatmap",
        merge_facet = T,
        multi.heatmap.col = list(c("grey95","#068DA9"),
                                 c("grey95","#C23373")))

Check the original heatmap:

tagHeatmap(seek_list)

3.4 Combined plot

ChipVis(object = mat_df,plot.type = "both")

Remove blank panels:

ChipVis(object = mat_df,plot.type = "both",merge_facet = T)