View source: R/computeOccupancy.R
computeOccupancy | R Documentation |
computeOccupancy
will compute the Occupancy from PWM Scores.
As described in detail in the vignette,
ChIPanalyser
uses PWM Scores, DNA Accessibility data, the number of
bound molecules and a sclaing factor of Transcription Factor specificty.
This function will compute occupancy using the
values assigned to each variable.
computeOccupancy(genomicProfiles,parameterOptions = NULL,
norm = TRUE, verbose = TRUE)
genomicProfiles |
|
parameterOptions |
|
norm |
|
verbose |
|
computeOccupancy
will compute the Occupancy from PWM Scores.
As described in detail in the vignette,
ChIPanalyser
uses PWM Scores, DNA Accessibility data,
the number of bound molecules and a sclaing factor of
Transcription Factor specificty.
This function will compute occupancy using the values assigned
to each variable. It should also be noted that the
parameterOptions
object contains a set of parameters used to compute Occupancy
(not only restricted to this ). These parameters are often dependant on
real ChIP-Seq data and will influence
the goodness of fit between the predicted model an real ChIP-seq data.
We strongly advise that the values assigned to each parameter should be
customiszed in order to increase the model ageement with
real world biological data.
computeOccupancy
will return a genomicProfiles
.
The main difference will reside in the
profiles
slot.
This slot is generally a list or GRangesList
.
Within these list type structures are enclosed
GRanges
containing the positions of site
above threshold, PWMScores and Occupancy for each site.
The series of GRanges will depend on the number of loci that are
tested and the number of element in the list will depend on the various
combinations of lambdaPWM
and boundMolecules
.
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.
#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)
OPP <- parameterOptions()
# Computing Genome Wide
GenomeWide <- computeGenomeWideScores(genomicProfiles = GPP,
DNASequenceSet = DNASequenceSet)
#Compute PWM Scores
PWMScores <- computePWMScore(genomicProfiles = GenomeWide,
DNASequenceSet = DNASequenceSet,
loci = top,
chromatinState = Access)
#Compute Occupnacy
Occupancy <- computeOccupancy(genomicProfiles = PWMScores,
parameterOptions = OPP)
Occupancy
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