regulatorySegmentsBiomart_ENSEMBL: Creates a binding motif track from ENSEMBL

Description Usage Arguments Value Author(s) References Examples

View source: R/BiofeatureGraphics.R

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

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regulatorySegmentsBiomart_ENSEMBL(gen, chr, start, end, featureDisplay = 'all', datasetEnsembl = "hsapiens_segmentation_feature")

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.Default=hsapiens_segmentation_feature

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

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library("Gviz")
gen <- "hg38"
chr <- "chr1"
start <- 10000
end <- 50000
featureDisplay <- "CTCF enriched"

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

####

library("Gviz")
gen <- "hg38"
chr <- "chr1"
start <- 10000
end <- 50000
featureDisplay <- c("CTCF enriched","Predicted Promoter Flank")

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

####

library("Gviz")
gen <- "hg38"
chr <- "chr1"
start <- 10000
end <- 50000
featureDisplay <- "all"
if(interactive()){
 regulatorySegmentsBiomartTrackAll<-regulatorySegmentsBiomart_ENSEMBL(gen,chr,start,end,featureDisplay)
  plotTracks(regulatorySegmentsBiomartTrackAll, from = start, to = end)
} else {
  data(regulatorySegmentsBiomartTrackAll)
  plotTracks(regulatorySegmentsBiomartTrackAll, from = start, to = end)

}

coMET documentation built on Nov. 23, 2017, 2:05 a.m.