samplePCA: Sample PCA plot for RNASeq

In polyak-lab/felipeCommonFunctions: Felipe Common Functions

Description

PCA plots of samples for DE analysis

Usage

samplePCA(expressionMatrix, numberOfPCs = 2, clusters = 1,
  autoClustering = FALSE, colorBy = "sample")

Arguments

expressionMatrix	Data frame with variance-stabilized expression data (in DESeq would be obtained by counts(dds, normalized = TRUE))
numberOfPCs	Integer value for number of principal components
clusters	User has the option of choosing how many clusters they want (k Means)
autoClustering	Boolean. If TRUE the function will determine the optimal number of k means
colorBy	User has "sample" and "cluster" options to determine which colors the plot

Value

List with 4 plots, 'variancePlot' has cumulative and individual importance of each PC, 'pcaGRid' is a grid of PCA plots, 'pca3dPlot' has 3D PCA, and 'clusteringPlot' is is the plot generated by eclust on the first 2 PCs

Author(s)

Felipe Flores

polyak-lab/felipeCommonFunctions documentation built on May 26, 2019, 12:32 a.m.