windowValues: Bins sequencing data for plotting
In sequenza: Copy Number Estimation from Tumor Genome Sequencing Data

Description Usage Arguments Details Value See Also Examples

Given a variable with corresponding genomic positions, the function bins the values in windows of a specified size and calculates weighted mean and 25th and 75th percentile for each window. The resulting object are visualized by the function plotWindows.

    windowValues(x, positions, chromosomes, window = 1e6, overlap = 0,
        weight = rep.int( x = 1, times = length(x)), start.coord = 1)
    windowBf(Af, Bf, good.reads, positions, chromosomes, window = 1e6,
        overlap = 0, start.coord = 1, conf = 0.95)

`x`	variable to be windowed.
`positions`	base-pair positions.
`chromosomes`	names or numbers of the chromosomes.
`window`	size of windows used for binning data. Smaller windows will take more time to compute.
`overlap`	integer defining the number of overlapping windows. Default is 0, no overlap.
`weight`	weights to be assigned to each value of `x`, usually related to the read depth.
`start.coord`	coordinate at which to start computing the windows. If NULL, will start at the first position available.
`Af`	A-allele frequency for the `Bf` calculation.
`Bf`	B-allele frequency for the `Bf` calculation.
`good.reads`	number of reads passing filter for the `Bf` calculation.
`conf`	confidence intervals of the binned `Bf` value.

DNA sequencing produces an amount of data too large to be handled by standard graphical devices. In addition, for samples analyzed with older machines and with low or middle coverage (20x to 50x), measures such as read depth are subject to big variations due to technical noise. Using windowValues prior to plotting reduces the noise and the amount of data to be plotted.

The binning of the B-allele frequency requires a separate function, windowBf, as the B-allele frequency calculation uses multiple values: Af, Bf and good.reads.

The output of windowValues and windowBf can be used as input for plotWindows.

a list of data.frame, one per chromosome. Each data.frame contains base-pair windows covering the chromosome. Each row of the data.frame correspond to a window and its weighted mean, 25th and 75th percentiles of the input values, and the number of data points within each window.

plotWindows

## Not run: 
    data.file <-  system.file("extdata", "example.seqz.txt.gz",
        package = "sequenza")
    seqz.data <- read.seqz(data.file)
    # 1Mb windows, each window is overlapping with 1 other
    # adjacent window: depth ratio
    seqz.ratio <- windowValues(x = seqz.data$depth.ratio,
        positions = seqz.data$position, chromosomes = seqz.data$chromosome,
        window = 1e6, weight = seqz.data$depth.normal, start.coord = 1,
        overlap = 1)

    seqz.hom  <- seqz.data$zygosity.normal == 'hom'
    seqz.het  <- seqz.data[!seqz.hom, ]
    # 1Mb windows, each window is overlapping with 1 other adjacent window:
    # B-allele frequency
    seqz.bafs  <- windowValues(x = seqz.het$Bf, positions = seqz.het$position,
        chromosomes = seqz.het$chromosome, window = 1e6,
        weight = seqz.het$depth.tumor, start.coord = 1, overlap = 1)
    # Repeat the same operation using windowBf
    seqz.bafs  <- windowBf(Af = seqz.het$Bf, Bf = seqz.het$Bf,
        good.reads = seqz.het$good.reads, positions = seqz.het$position,
        chromosomes = seqz.het$chromosome, window = 1e6,
        start.coord = 1, overlap = 1, conf = 0.95)

## End(Not run)