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.

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 = TRUE)