PCAplot | R Documentation |
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)
exploredds |
object of class |
plotly |
logical: when |
savePlot |
logical: when |
filePlot |
file name where the plot will be saved. For more information,
please consult the |
returns an object of ggplot
or plotly
class.
## 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)
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