searchSites: Searching function for Sites above threshold and predicted...
In ChIPanalyser: ChIPanalyser: Predicting Transcription Factor Binding Sites

Description Usage Arguments Details Value Author(s) References Examples

View source: R/GenomicProfileGenericFunctions.R

searchSites is function enabling quick extraction and search for parameter combinations and/or loci in any genomicProfiles object from computeOccupancy onwards.

1	searchSites(Sites,lambdaPWM="all",BoundMolecules="all", Locus="all")

`Sites`	`Sites` is either a `genomicProfiles` or the result of `computeOptimal`
`lambdaPWM`	`lambdaPWM` is a numeric vector describing the ScalingFactors that should be searched within `Sites`.
`BoundMolecules`	`BoundMolecules` is a numeric vector describing the BoundMolecules that should be searched within `Sites`.
`Locus`	`Locus` is a character vector describing the Loci that should be searched within Sites.

When testing numerous combinations of lambdaPWM and boundMolecules on top of many loci, it can become challenging to navigate the large data output searchSites will make searching in this slot a lot easier. If all arguments are left at their default value of "all", then all Parameters will be searched thus returning the full list of Sites above threshold. If a value for lambdaPWM is user provided then only this lambdaPWM will be selected (all boundMolecules and loci will also be selected). searchSites also works on the result of computeOptimal.

Returns object of same time as parsed to this function with only the parameters and/or loci selected.

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<e2><80><93>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 genomicProfiles object
  GPP <- genomicProfiles(PFM=PFM, BPFrequency=DNASequenceSet)


  # Computing Genome Wide
  GenomeWide <- computeGenomeWideScore(genomicProfiles = GPP,
      DNASequenceSet = DNASequenceSet)

  #Compute PWM Scores
  PWMScores <- computePWMScore(genomicProfiles = GenomeWide,
       DNASequenceSet = DNASequenceSet, loci = eveLocus, chromatinState = Access)
  #Compute Occupnacy
  Occupancy <- computeOccupancy(genomicProfiles = PWMScores)
  searchSites(Occupancy,ScalingFactor=c(1,4), BoundMolecules = c(1,100),
      Locus="eve")

  #Compute ChIP profiles
  chipProfile <- computeChIPProfile(genomicProfiles=Occupancy,loci=eveLocus)
  searchSites(chipProfile,ScalingFactor=c(1,4), BoundMolecules = c(1,100),
      Locus="eve")

optimalParam <- computeOptimal(genomicProfiles = GPP,
        DNASequenceSet = DNASequenceSet,
        ChIPScore = eveLocusChip,
        chromatinState = Access,
        parameterOptions = OPP,
        parameter = "all",
        peakMethod="moving_kernel")

searchSites(optimalParam,ScalingFactor=c(1,4), BoundMolecules = c(1,100),
    Locus="eve")