RegulatorySegmentsBiomart: Creates a binding motif track from ENSEMBL

In TiphaineCMartin/coMET_original: coMET: visualisation of regional epigenome-wide association scan (EWAS) results and DNA co-methylation patterns.

Description

Creates a track of regulatory segments from ENSEMBL using the Gviz bioconductor package. A complete list of features and their associated colours can be found in the user guide.

Usage

RegulatorySegmentsBiomart(gen, chr, start, end, featureDisplay)

Arguments

gen	The name of the genome. Currently only handles human data from either the previous version, GRCh37 (also known as hg19) or the current version, GRCh38 (also known as hg38).
chr	The chromosome of interest
start	The starting position in the region of interest (the smallest value)
end	The end position in the region of interest (the largest value)
featureDisplay	A vector of regulatory features to be displayed, such as Predicted heterochomatin. Spelling and capitalisation of features must be identical to those in the user guide. There are three possibilities. First, the visualisation of only one feature (e.g. featureDisplay <- "Predicted heterochomatin"), only the name of the specific feature is required. Second, visualisation of a set of features, for this a vector of features is required (e.g. featureDisplay <- c("Predicted low activity","Predicted heterochomatin")). Finally, visualison all features in the genomic region, achived by using the word "all" (e.g. featureDisplay <- "all"), "all" is set by default. You can find the complete list of features and their associated colours in the user guide.
datasetEnsembl	Allows the user to manually set which data set is used if required.

Value

An AnnotationTrack object of Gviz

Author(s)

Tiphaine Martin

Tom Hardiman

References

http://bioconductor.org/packages/release/bioc/html/Gviz.html

Got to ENSEMBLregulation binding motif biomart

Examples

library("Gviz")
gen <- "hg19"
chr <- "chr1"
start <- 10000
end <- 50000
featureDisplay <- "Predicted heterochomatin"

if(interactive()){
 RegulatorySegmentsBiomartTrackSingle<-RegulatorySegmentsBiomart(gen,chr,start,end,featureDisplay)
  plotTracks(RegulatorySegmentsBiomartTrackSingle, from = start, to = end)
} else {
  data(RegulatorySegmentsBiomartTrackSingle)
  plotTracks(RegulatorySegmentsBiomartTrackSingle, from = start, to = end)
}

------------------------------------------------------------------------------

library("Gviz")
gen <- "hg19"
chr <- "chr1"
start <- 10000
end <- 50000
featureDisplay <- c("Predicted heterochomatin","Predicted low activity")

if(interactive()){
 RegulatorySegmentsBiomartTrackMultiple<-RegulatorySegmentsBiomart(gen,chr,start,end,featureDisplay)
  plotTracks(RegulatorySegmentsBiomartTrackMultiple, from = start, to = end)
} else {
  data(RegulatorySegmentsBiomartTrackMultiple)
  plotTracks(RegulatorySegmentsBiomartTrackMultiple, from = start, to = end)
}

------------------------------------------------------------------------------

library("Gviz")
gen <- "hg19"
chr <- "chr1"
start <- 10000
end <- 50000
featureDisplay <- "all"
if(interactive()){
 RegulatorySegmentsBiomartTrackAll<-RegulatorySegmentsBiomart(gen,chr,start,end,featureDisplay)
  plotTracks(RegulatorySegmentsBiomartTrackAll, from = start, to = end)
} else {
  data(RegulatorySegmentsBiomartTrackAll)
  plotTracks(RegulatorySegmentsBiomartTrackAll, from = start, to = end)

}

TiphaineCMartin/coMET_original documentation built on May 9, 2019, 4:49 p.m.