plotOptimalHeatMaps {ChIPanalyser}R Documentation

Heat Map of optimal Parameters

Description

plotOptimalHeatMaps will plot heat maps of optimal Parameters and highlight the optimal combination of ScalingFactorPWM and boundMolecules

Usage

plotOptimalHeatMaps(optimalParam,contour=TRUE,col=NULL,main=NULL,layout=TRUE)

Arguments

optimalParam

optimalParam is a list containing containing optimal matricies (or only one if only one paramter was selected). These matricies are the result of the computeOptimal function

contour

parameter is logical. Should contour lines be plotted?

col

col vector of colours to be used for each heat map. If none are specified, rainbow colours will be used. NOTE: colour vector will be recyled if not enough colours are provided.

main

main title.

layout

layout is either TRUE or FALSE specifying if stadard layout should be used or not. If TRUE, each heat map will be plotted on an individual page with a heat map scale of the right side.

Details

Once the optimal set of Parameters ( ScalingFactorPWM and boundMolecules ), it is possible to plot the results in the form of a heat map. Each heat map will be plotted in a seperate page if layout = TRUE, If layout= FALSE, it is up to the user to define how they wish to layout there heat maps.

Value

Returns a heat map of optimal combinations of ScalingFactorPWM and boundMolecules. The x axis represents the different value assigned to lambda ( ScalingFactorPWM ) and the y axis represents the different values to boundMolecules ( boundMolecules ).

Author(s)

Patrick C. N. Martin <pm16057@essex.ac.uk>

References

Zabet NR, Adryan B (2015) Estimating binding properties of transcription factors from genome-wide binding profiles. Nucleic Acids Res., 43, 84–94.

Examples


#Data extraction
data(ChIPanalyserData)
# path to Position Frequency Matrix
PFM <- file.path(system.file("extdata",package="ChIPanalyser"),"BCDSlx.pfm")
#As an example of genome, this example will run on the Drosophila genome

if(!require("BSgenome.Dmelanogaster.UCSC.dm3", character.only = TRUE)){
    if (!requireNamespace("BiocManager", quietly=TRUE))
        install.packages("BiocManager")
    BiocManager::install("BSgenome.Dmelanogaster.UCSC.dm3")
    }
library(BSgenome.Dmelanogaster.UCSC.dm3)
DNASequenceSet <- getSeq(BSgenome.Dmelanogaster.UCSC.dm3)

#Building data objects
GPP <- genomicProfileParameters(PFM=PFM,BPFrequency=DNASequenceSet)
OPP <- occupancyProfileParameters()
#Computing Optimal set of Parameters
optimalParam <- computeOptimal(DNASequenceSet = DNASequenceSet,
    genomicProfileParameters = GPP,
    LocusProfile = eveLocusChip,
    setSequence = eveLocus,
    DNAAccessibility = Access,
    occupancyProfileParameters = OPP,
    optimalMethod = "all")
plotOptimalHeatMaps(optimalParam)
[Package ChIPanalyser version 1.4.0 Index]