addPeaks: Add predefined peaks to a simulated 4C-seq sample
In walter-ca/Basic4CSim: Basic4CSim: Simulation of 4C-seq data

Description Usage Arguments Value Author(s) Examples

This helper function adds predefined regions of higher signal (peaks) in near-cis to a 4C-seq sample. Random noise as well as modifiers for blind fragments can be added.

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addPeaks(simTable, randomPeaks, vpStart, maxVPArea = 7500, sdVP = 2000, 
vpRegionDist = 100000, minRandomVPPeak = -500, maxRandomVPPeak = 500, 
chanceRandom = 0.8, differenceRandom = 0.2)

`simTable`	virtual simulation fragment library
`randomPeaks`	list of peaks to be simulated: ID (e.g. number), mean (genomic coordinate), max (maximum signal for the peak in question), sd (standard deviation, "width")
`vpStart`	viewpoint position
`maxVPArea`	height of viewpoint peak (with possible exception of actual viewpoint fragment)
`sdVP`	width of viewpoint peak
`vpRegionDist`	length of near-cis region where randomly generated peaks are simulated
`minRandomVPPeak`	minimum for randomly chosen summand to fragment read count (can be negative)
`maxRandomVPPeak`	maximum for randomly chosen summand to fragment read count (can be negative)
`chanceRandom`	chance for occurrence of random summands
`differenceRandom`	parameter to manipulate peak heights per peak: (1-dR) <= max <= (1+dR)

Data frame with added intervals of higher signal (peaks) in near-cis

Carolin Walter

    if(interactive()) {
        simTableFile <- system.file("extdata", "simTable_bg.csv", 
            package="Basic4CSim")
        simTable = read.csv(simTableFile, sep = "\t", header = TRUE)
        vpStart = 69999869
        set.seed(42)
        randomPeaks = makeRandomPeaks(peakNumber=6, vpStart)
        simTable = addPeaks(simTable, randomPeaks, vpStart)
        head(simTable)
    }