plotPCAVar {MatrixQCvis} | R Documentation

## Plot of explained variance against the principal components

### Description

The function 'plotPCAVar' plots the explained variance (in against the principal components for the measured and permuted values.

### Usage

    plotPCAVar(var_x, var_perm = NULL)

### Arguments

`var_x` | 'numeric' (named 'numeric' vector)
`var_perm` | 'matrix' with the explained variance obtained by permutation (function 'permuteExplVar')

### Details

The argument 'var_perm' is optional and visualization of permuted values can be omitted by setting 'var_perm = NULL'.

### Value

'gg' object from 'ggplot'

### Author(s)

Thomas Naake

### Examples

    x <- matrix(1:100, ncol = 10)
    var_x <- explVar(x = x, params = list(center = TRUE, scale = TRUE),
        type = "PCA")
    var_perm <- permuteExplVar(x = x, n = 100, center = TRUE, scale = TRUE)
    plotPCAVar(var_x = var_x, var_perm = var_perm)

[Package MatrixQCvis version 1.0.0 Index]