pca {M3C} | R Documentation

## pca: A principal component analysis function

### Description

pca: A principal component analysis function

### Usage

    pca(mydata, K = FALSE, printres = FALSE, labels = FALSE,
      text = FALSE, axistextsize = 18, legendtextsize = 18,
      dotsize = 5, textlabelsize = 4)

### Arguments

`mydata` | Data frame or matrix or M3C results object: if dataframe/matrix should have samples as columns and rows as features
`K` | Numerical value: if running on the M3C results object, which value was the optimal K?
`printres` | Logical flag: whether to print the PCA into current directory
`labels` | Character vector: if we want to just label with gender for example
`text` | Character vector: if we wanted to label the samples with text IDs to look for outliers
`axistextsize` | Numerical value: axis text size
`legendtextsize` | Numerical value: legend text size
`dotsize` | Numerical value: dot size
`textlabelsize` | Numerical value: text inside plot label size

### Value

A PCA plot object

### Examples

    PCA <- pca(mydata)

[Package M3C version 1.6.0 Index]