NOISeq (version 2.16.0)

PCA.GENES: Principal Component Analysis

Description

Computes a Principal Component Analysis on any data matrix.

Usage

PCA.GENES(X)

Arguments

X

Matrix or data.frame with variables (e.g. genes) in columns and observations (e.g. samples) in rows.

Examples

	## Simulate data matrix with 500 variables and 10 observations
	datasim = matrix(sample(0:100, 5000, replace = TRUE), nrow = 10)

	## PCA
	myPCA = PCA.GENES(datasim)

	## Extracting the variance explained by each principal component
	myPCA$var.exp