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 = 30, legendtextsize = 30,
  dotsize = 6, 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 1.4.1 Index]