View source: R/plotOccupancy.R
plotOccupancyProfile | R Documentation |
plotOccupancyProfile
plots the predicted profiles.
If provided, this functions will also plot ChIP-seq profiles,
PWMScores (or Occupancy), chromatin States, Goodness of Fit estimates and gene information.
plotOccupancyProfile(predictedProfile, ChIPScore = NULL,chromatinState = NULL,
occupancy = NULL,goodnessOfFit = NULL,PWM=FALSE,
geneRef = NULL,addLegend = TRUE,...)
predictedProfile |
|
ChIPScore |
|
chromatinState |
|
occupancy |
|
goodnessOfFit |
|
PWM |
|
geneRef |
|
addLegend |
|
... |
Any other graphical Parameter of the following : cex, cex.lab, cex.main, densityCS , densityGR , ylab, xlab, main, colPred, colChIP, colOccup, colCS, colGR, n_axis_ticks. See details. |
Once the predicted ChIP-seq like profiles have been computed, it is possible to plot these profiles.
This functions allows to control graphical parameters. In short:
* col = color values - exact number of colors or colors that will be used in a colorRampPalettte.
* cex = font sizes - for text, axis labels and main
* Density = fill density for chromatin state and/or geneRef blocks
Pred = predictedProfile ChIP = ChIP score (Experimental ChIP data) CS = Chromatin States GR = Gene reference Occup = Occupnacy locations
Returns a profile plot with "Occupancy" on the y axis and DNA position on the the X- axis.
Patrick C.N. Martin <pcnmartin@gmail.com>
Zabet NR, Adryan B (2015) Estimating binding properties of transcription factors from genome-wide binding profiles. Nucleic Acids Res., 43, 84–94. Patrick C.N. Martin and Nicolae Radu Zabe (2020) Dissecting the binding mechanisms of transcription factors to DNA using a statistical thermodynamics framework. CSBJ, 18, 3590-3605.
#Data extraction
data(ChIPanalyserData)
# path to Position Frequency Matrix
PFM <- file.path(system.file("extdata",package="ChIPanalyser"),"BEAF-32.pfm")
#As an example of genome, this example will run on the Drosophila genome
if(!require("BSgenome.Dmelanogaster.UCSC.dm6", character.only = TRUE)){
if (!requireNamespace("BiocManager", quietly=TRUE))
install.packages("BiocManager")
BiocManager::install("BSgenome.Dmelanogaster.UCSC.dm6")
}
library(BSgenome.Dmelanogaster.UCSC.dm6)
DNASequenceSet <- getSeq(BSgenome.Dmelanogaster.UCSC.dm6)
#Building data objects
GPP <- genomicProfiles(PFM=PFM,PFMFormat="JASPAR", BPFrequency=DNASequenceSet)
# Computing Genome Wide
GenomeWide <- computeGenomeWideScores(DNASequenceSet = DNASequenceSet,
genomicProfiles = GPP)
#Compute PWM Scores
PWMScores <- computePWMScore(DNASequenceSet = DNASequenceSet,
genomicProfiles = GenomeWide,
loci = top, chromatinState = Access)
#Compute Occupnacy
Occupancy <- computeOccupancy(genomicProfiles = PWMScores)
#Compute ChIP profiles
chipProfile <- computeChipProfile(loci = top,
genomicProfiles = Occupancy)
#Plotting Profile
plotOccupancyProfile(predictedProfile=chipProfile,
ChIPScore = chip,
chromatinState = Access,
occupancy = Occupancy,
geneRef =geneRef)
plotOccupancyProfile(predictedProfile=chipProfile,
ChIPScore = chip,
chromatinState = Access,
occupancy = Occupancy,
geneRef = geneRef,
colCS = c("red","blue"),
densityGR = 60)
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