pcaScoresFromLogFC: Perform principal component analysis and derive PCA scores...

In bedapub/ribiosPlot: Plotting module of ribios for visualization

Perform principal component analysis and derive PCA scores from a logFC matrix

Description

Perform principal component analysis and derive PCA scores from a logFC matrix

Usage

pcaScoresFromLogFC(lfcMat, reference = 0, choices, reverse = c(FALSE, FALSE))

Arguments

lfcMat	Log fold-chnage matrix, genes (features) in rows and samples in columns
reference	The reference value that should be set as 0 in the scores, default: 0
choices	How many PCs should be retured. Passed to pcaScores
reverse	Whether the axes should be reversed. Passed to pcaScores Perform PCA and get scores from a logFC matrix by setting a pseudo profile of no change (0 for all features) at the origin point

Examples

lfcMat <- matrix(rnorm(9), nrow=3)
pcaScoresFromLogFC(lfcMat)

bedapub/ribiosPlot documentation built on Sept. 1, 2023, 6:50 p.m.