plotPCA {facopy} | R Documentation

## facopy PCA

### Description

Plot a PCA of the samples based on their similarity given a certain set of alterations.

### Usage

    plotPCA(fad, alteration, varName, sel = NULL,
            design = c("binary", "versus", "lvog")[1],
            do.plot = TRUE, by.size = TRUE, cex = 4)

### Arguments

`fad` | `facopyInfo` object with a certain study's `facopy` data.
`alteration` | A character describing the kinds of alteration to include. It should be one of the following: - `amplifications` All amplifications (CN>2). - `deletions` All deletions (CN<2). - `loh` All loss of heterozygosity (LOH), regardless of copy number. - `cnas` All copy number alterations (CN<>2). - `any` Any kind of alteration. - `all` Any kind of alteration, same as `any`. - `onlygain` Only non-LOH amplifications. - `someloss` All deletions plus LOH alterations.
`varName` | A character indicating the variable of interest within the `facopyInfo` object. Points representing samples in the PCA will be colored according to the classification in such variable. Call `summary` on your `facopyInfo` object to see the names of defined variables.
`sel` | A character vector with the chromosome arms that will be taken into account in the analysis. Example: `c("1q","9p")`.
`design` | Depending on the chosen alteration, different designs are available. The simplest design is `binary`: an alteration exists or it does not. The `versus` design, for CNAs, assigns a value of -1, 0 or 1 depending on whether a deletion, no copy number change or an amplification exists for a given feature. The `vlog` design, for all (any) alterations, assigns a value of -1, 0 or 1 depending on whether a deletion or LOH, no copy number change or an amplification without LOH exists.
`do.plot` | A logical indicating whether to produce graphical output.
`by.size` | A logical indicating whether the width of the points' border represents the frequency of the selected alterations.
`cex` | A numerical value giving the amount by which points in the plot should be scaled relative to the base size. Default is 4.

### Value

The results of the PCA are returned and the graphical output is optional.

### Author(s)

David Mosen-Ansorena

### Examples

    data(myStudy) # load example study

    pca = plotPCA(myStudy, "any", "stage")
    head(pca$eig)

[Package facopy version 1.13.0 Index]