dataPlot: Plot different graphs depending on the current step of...

In KnowSeq: KnowSeq R/Bioc package: The Smart Transcriptomic Pipeline

Description

This function allows to plot different charts only by changing the parameters, for the different KnowSeq pipeline steps. Furthermore, the chosen plot can be saved to PNG and PDF.

Usage

dataPlot(
  data,
  labels,
  colours = c("red", "green"),
  main = "",
  ylab = "Expression",
  xlab = "Samples",
  xgrid = FALSE,
  ygrid = FALSE,
  legend = "",
  mode = "boxplot",
  heatmapResultsN = 0,
  toPNG = FALSE,
  toPDF = FALSE
)

Arguments

data	Normally, the data parameter is an expression matrix or data.frame, however for the confusionMatrix plot, the data are a confussion matrix that can be achieved by using the output of any of the machine learning functions of this package.
labels	A vector or factor that contains the labels for each of the samples in the data parameter.
colours	A vector that contains the desired colours to plot the different charts. Example: c("red","green","blue").
main	The title for the plot.
ylab	The description for the y axis.
xlab	The description for the x axis.
xgrid	Shows the x grid into the plot
ygrid	Shows the y grid into the plot
legend	A vector with the elements in the legend of the plot.
mode	The different plots supported by this package. The possibilities are boxplot, orderedBoxplot, genesBoxplot, heatmap, confusionMatrix, classResults and heatmapResults.
heatmapResultsN	Number of genes to show when mode is equal to heatmapResults.
toPNG	Boolean variable to indicate if a plot would be save to PNG.
toPDF	Boolean variable to indicate if a plot would be save to PDF.

Value

Nothing to return.

Examples

dir <- system.file("extdata", package="KnowSeq")
load(paste(dir,"/expressionExample.RData",sep = ""))

dataPlot(expressionMatrix,labels,mode = "boxplot",toPNG = TRUE,toPDF = TRUE)
dataPlot(DEGsMatrix[1:12,],labels,mode = "orderedBoxplot",toPNG = TRUE,toPDF = TRUE)
dataPlot(DEGsMatrix[1:12,],labels,mode = "genesBoxplot",toPNG = TRUE,toPDF = FALSE)
dataPlot(DEGsMatrix[1:12,],labels,mode = "heatmap",toPNG = TRUE,toPDF = TRUE)

results <- knn_trn(t(DEGsMatrix), labels, rownames(DEGsMatrix), 3)
dataPlot(results, labels = "", mode = "heatmapResults", main = "Plot to show indicators of trained model")

KnowSeq documentation built on April 16, 2021, 6:01 p.m.