PCAplot: PCAplot

In systemPipeR/spsBio: spsBio: A systemPipeShiny plugin for biological data visualization

Description

This function plots a Principal Component Analysis (PCA) from transformed expression matrix. This plot shows samples variation based on the expression values and identifies batch effects.

Usage

PCAplot(exploredds, plotly = FALSE, savePlot = FALSE, filePlot = NULL)

Arguments

exploredds	object of class DESeq2::DESeqTransform().
plotly	logical: when FALSE (default), the ggplot2 plot will be returned. TRUE option returns the plotly version of the plot.
savePlot	logical: when FALSE (default), the plot will not be saved. If TRUE the plot will be saved, and requires the filePlot argument.
filePlot	file name where the plot will be saved. For more information, please consult the ggplot2::ggsave() function.

Value

returns an object of ggplot or plotly class.

Examples

## Targets file
targetspath <- system.file("extdata", "targets.txt", package="systemPipeR")
targets <- read.delim(targetspath, comment="#")
cmp <- systemPipeR::readComp(file=targetspath, format="matrix", delim="-")
## Count table file
countMatrixPath <- system.file("extdata", "countDFeByg.xls", package="systemPipeR")
countMatrix <- read.delim(countMatrixPath, row.names=1)
## Plot
exploredds <- exploreDDS(countMatrix, targets, cmp=cmp[[1]], preFilter=NULL, transformationMethod="rlog")
PCAplot(exploredds, plotly = FALSE)
PCAplot(exploredds, plotly = TRUE)
PCAplot(exploredds, save = TRUE, filePlot = "pca.pdf")

systemPipeR/spsBio documentation built on Oct. 2, 2020, 9:30 a.m.