plot.pcair {GENESIS} | R Documentation

## PC-AiR: Plotting PCs

### Description

`plot.pcair` is used to plot pairs of principal components contained in a class '`pcair`' object obtained as output from the `pcair` function.

### Usage

    ## S3 method for class 'pcair'
    plot(x, vx = 1, vy = 2, pch = NULL, col = NULL,
            xlim = NULL, ylim = NULL, main = NULL, sub = NULL,
            xlab = NULL, ylab = NULL, ...)

### Arguments

`x` | An object of class '`pcair`' obtained as output from the `pcair` function.
`vx` | An integer indicating which principal component to plot on the x-axis; the default is 1.
`vy` | An integer indicating which principal component to plot on the y-axis; the default is 2.
`pch` | Either an integer specifying a symbol or a single character to be used in plotting points. If `NULL`, the default is dots for the 'unrelated subset' and + for the 'related subset'.
`col` | A specification for the plotting color for points. If `NULL`, the default is black for the 'unrelated subset' and blue for the 'related subset'.
`xlim` | The range of values shown on the x-axis. If `NULL`, the default shows all points.
`ylim` | The range of values shown on the y-axis. If `NULL`, the default shows all points.
`main` | An overall title for the plot. If `NULL`, the default specifies which PC-AiR PCs are plotted.
`sub` | A sub title for the plot. If `NULL`, the default is none.
`xlab` | A title for the x-axis. If `NULL`, the default specifies which PC-AiR PC is plotted.
`ylab` | A title for the y-axis. If `NULL`, the default specifies which PC-AiR PC is plotted.
`...` | Other parameters to be passsed through to plotting functions, (see `par`).

### Details

This function provides a quick and easy way to plot principal components obtained with the function `pcair` to visualize the population structure captured by PC-AiR.

### Value

A figure showing the selected principal components plotted against each other.

### Author(s)

Matthew P. Conomos

### See Also

`pcair` for obtaining principal components that capture population structure in the presence of relatedness. `par` for more in depth descriptions of plotting parameters. The generic function `plot`.

### Examples

    library(GWASTools)

    # file path to GDS file
    gdsfile <- system.file("extdata", "HapMap_ASW_MXL_geno.gds", package="GENESIS")
    # read in GDS data
    HapMap_geno <- GdsGenotypeReader(filename = gdsfile)
    # create a GenotypeData class object
    HapMap_genoData <- GenotypeData(HapMap_geno)
    # load saved matrix of KING-robust estimates
    data("HapMap_ASW_MXL_KINGmat")
    # run PC-AiR
    mypcair <- pcair(genoData = HapMap_genoData, kinMat = HapMap_ASW_MXL_KINGmat,
                    divMat = HapMap_ASW_MXL_KINGmat)
    # plot top 2 PCs
    plot(mypcair)
    # plot PCs 3 and 4
    plot(mypcair, vx = 3, vy = 4)
    close(HapMap_genoData)

[Package GENESIS version 2.10.1 Index]