profileAccuracyEstimate {ChIPanalyser} | R Documentation |
profileAccuracyEstimate
will compare the predicted ChIP-seq-like
profile to real ChIP-seq data and return a set of metrics describing how
accurate the predicted model is compared to real data.
profileAccuracyEstimate(LocusProfile, predictedProfile, occupancyProfileParameters = NULL,method="all")
LocusProfile |
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predictedProfile |
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occupancyProfileParameters |
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method |
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In order to assess the quality of the model against experimental ChIP-seq data, ChIPanalyser offers a wide range of method to choose from. These methods are also used when computing optimal paramters.
Returns a list of two elements. The first element represents lists containing the model quality assessments for every combination of parameters (Bound Molecules and lambda) for every genomic region. The second element of the list contains the result of the ROCR package: False positives, False Negative, etc... See ROCR package.
Patrick C. N. Martin <pm16057@essex.ac.uk>
Zabet NR, Adryan B (2015) Estimating binding properties of transcription factors from genome-wide binding profiles. Nucleic Acids Res., 43, 84–94.
#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 Genome Wide GenomeWide <- computeGenomeWidePWMScore(DNASequenceSet = DNASequenceSet, genomicProfileParameters = GPP) #Compute PWM Scores PWMScores <- computePWMScore(DNASequenceSet = DNASequenceSet, genomicProfileParameters = GenomeWide, setSequence = eveLocus, DNAAccessibility = Access) #Compute Occupnacy Occupancy <- computeOccupancy(AllSitesPWMScore = PWMScores, occupancyProfileParameters = OPP) #Compute ChIP profiles chipProfile <- computeChipProfile(setSequence = eveLocus, occupancy = Occupancy, occupancyProfileParameters = OPP) #Estimating accuracy estimate AccuracyEstimate <- profileAccuracyEstimate(LocusProfile = eveLocusChip, predictedProfile = chipProfile, occupancyProfileParameters = OPP)