heatTargetAnnotation-methods: Plots the percentage of overlapping intervals with genomic...
In BIMSBbioinfo/genomation: Summary, annotation and visualization of genomic data

Description Usage Arguments Value See Also Examples

This function plots a heatmap for percentage of overlapping ranges with provided genomic features. The input object is a list of AnnotationByFeature objects, which contains necessary information about overlap statistics to make the plot.

1 2	heatTargetAnnotation(l, cluster = FALSE, col = c("white", "blue"), precedence = FALSE, plot = TRUE)

`l`	a `list` of `AnnotationByFeature` objects. This could be returned by `annotateWithFeatures` function.
`cluster`	TRUE/FALSE. If TRUE the heatmap is going to be clustered using a default hierarchical clustering scheme.
`col`	a vector of two colors that will be used for interpolation. The first color is the lowest one, the second is the highest one
`precedence`	TRUE\|FALSE. If TRUE the precedence of annotation features will be used when plotting. The precedence will be taken from the GRangesList used as annotation. The first GRanges will be treated as most important, and the second as the second most important and so on. Such that, if an interval overlaps with features on that is part of the first GRanges object in the annotation GRangesList, the rest of its overlaps with other elements in the annotation GRangesList will be ignored. This feature is important to have if the user desires that percentage of overlaps adds up to 100. This is only possible when the annotation features are non-overlaping with eachother or there is a hierarchy/precedence among them such as (with promoter>exon>intron precedence). In this case, anything that overlaps with a promoter annotation will only be counted as promoter even if it overlaps with exons or introns.
`plot`	If FALSE, does not plot the heatmap just returns the matrix used to make the heatmap

returns the matrix used to make the heatmap when plot FALSE, otherwise returns ggplot2 object which can be modified further.

see getMembers, annotateWithFeatures

library(GenomicRanges)
data(cage)
data(cpgi)
cage$tpm=NULL
gl = GRangesList(cage=cage, cpgi=cpgi)

bed.file = system.file("extdata/chr21.refseq.hg19.bed", package = "genomation")
gene.parts = readTranscriptFeatures(bed.file)
annot = annotateWithFeatures(gl, gene.parts, intersect.chr=TRUE)

            
  
heatTargetAnnotation(annot)