SARTools (version 1.6.2)

PCAPlot: PCA of samples (if use of DESeq2)

Description

Principal Component Analysis of samples based on the 500 most variant features on VST- or rlog-counts (if use of DESeq2)

Usage

PCAPlot(counts.trans, group, n = min(500, nrow(counts.trans)),
  col = c("lightblue", "orange", "MediumVioletRed", "SpringGreen"),
  outfile = TRUE)

Arguments

counts.trans

a matrix a transformed counts (VST- or rlog-counts)

group

factor vector of the condition from which each sample belongs

n

number of features to keep among the most variant

col

colors to use (one per biological condition)

outfile

TRUE to export the figure in a png file

Value

A file named PCA.png in the figures directory with a pairwise plot of the three first principal components