intensityOutliersPlot {GWASTools} | R Documentation

## Plot mean intensity and highlight outliers

### Description

`intensityOutliersPlot` is a function to plot mean intensity for chromosome i vs mean of intensities for autosomes (excluding i) and highlight outliers

### Usage

    intensityOutliersPlot(mean.intensities, sex, outliers,
    	              sep = FALSE, label, ...)

### Arguments

`mean.intensities` | scan x chromosome matrix of mean intensities
`sex` | vector with values of "M" or "F" corresponding to scans in the rows of `mean.intensities`
`outliers` | list of outliers, each member corresponds to a chromosome (member "X" is itself a list of female and male outliers)
`sep` | plot outliers within a chromosome separately (TRUE) or together (FALSE)
`label` | list of plot labels (to be positioned below X axis) corresponding to list of outliers
`...` | additional arguments to `plot`

### Details

Outliers must be determined in advance and stored as a list, with one element per chromosome. The X chromosome must be a list of two elements, "M" and "F". Each element should contain a vector of ids corresponding to the row names of `mean.intensities`.

If `sep=TRUE`, `labels` must also be specified. `labels` should be a list that corresponds exactly to the elements of `outliers`.

### Author(s)

Cathy Laurie

### See Also

`meanIntensityByScanChrom`

### Examples

    # calculate mean intensity
    library(GWASdata)
    file <- system.file("extdata", "illumina_qxy.gds", package="GWASdata")
    gds <- GdsIntensityReader(file)
    data(illuminaScanADF)
    intenData <- IntensityData(gds, scanAnnot=illuminaScanADF)
    meanInten <- meanIntensityByScanChrom(intenData)
    intenMatrix <- meanInten$mean.intensity

    # find outliers
    outliers <- list()
    sex <- illuminaScanADF$sex
    id <- illuminaScanADF$scanID
    allequal(id, rownames(intenMatrix))
    for (i in colnames(intenMatrix)) {
      if (i != "X") {
        imean <- intenMatrix[,i]
        imin <- id[imean == min(imean)]
        imax <- id[imean == max(imean)]
        outliers[[i]] <- c(imin, imax)
      } else {
        idf <- id[sex == "F"]
        fmean <- intenMatrix[sex == "F", i]
        fmin <- idf[fmean == min(fmean)]
        fmax <- idf[fmean == max(fmean)]
        outliers[[i]][["F"]] <- c(fmin, fmax)
        idm <- id[sex == "M"]
        mmean <- intenMatrix[sex == "M", i]
        mmin <- idm[mmean == min(mmean)]
        mmax <- idm[mmean == max(mmean)]
        outliers[[i]][["M"]] <- c(mmin, mmax)
      }
    }

    par(mfrow=c(2,4))
    intensityOutliersPlot(intenMatrix, sex, outliers)
    close(intenData)

[Package GWASTools version 1.32.0 Index]