computeChipProfile {ChIPanalyser} | R Documentation |
computeChipProfile
compute ChIP-seq like profile from occupancy data.
Occupancy data is computed using computeOccupancy
.
computeChipProfile(setSequence, occupancy, occupancyProfileParameters = NULL, norm = TRUE, method = c("moving_kernel","truncated_kernel","exact"), peakSignificantThreshold= NULL,cores=1, verbose = TRUE)
setSequence |
|
occupancy |
|
occupancyProfileParameters |
|
norm |
|
method |
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peakSignificantThreshold |
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cores |
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verbose |
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computeChipProfile
converts Transcription Factor occuapncy to a profile
resembling the one of a ChIP-seq profile. A certain set of Parameters are
required in order to build ChIP profiles.
These Parameters are defined and storedin a
occupancyProfileParameters
object. These parameters are:
chipMean
, chipSd
, chipSmooth
,
stepSize
,backgroundSignal
,
maxSignal
and removeBackground
.
All these Parameters have default values already stored.
However, for an optimal fit, it is advised to derive these values
from actual ChIP-seq data.
For more information on these parameters,
see occupancyProfileParameters
.
This functions also requires a set of sequencesin form of a
GRanges
. The sequence set are the loci of interest
on which the ChIP-seq profile will be computed.
Returns a list containing all ChIP-seq like profile for every combination of
ScalingFactorPWM
and boundMolecules
.
The correlation and Mean Squared Error between the prdicted ChIP profile
and actual ChIP-seq profile for the same loci
will vary depending on the value given for ScalingFactorPWM
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.
#Extracting Data 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 genomicProfileParameters object 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) chipProfile