In this post I show how groupScatterPlot(), function of the rnatoolbox R package can be used for plotting the individual values in several groups together with their mean (or other statistics). I think this is a useful function for plotting grouped data when some groups (or all groups) have few data points ! You may be wondering why to include such function in the rnatoolbox package ?! Well ! I happen to use it quit a bit for plotting expression values of different groups of genes/transcripts in a sample or expression levels of a specific gene/transcript in several sample groups. These expression value are either FPKM, TPM, LCPM, or PSI values (Maybe I should go through these different normalizations later in a different post 😐!). But of course its application is not restricted to gene expression or RNAseq data analysis.

For the test, I first generate a list with three random values. The values are generated randomly using normal distribution, featuring different means and standard deviations.

library(rnatoolbox)
datList<- list(
  l1=rnorm(n=30, mean = 10, sd = 3),
  l2=rnorm(n=20, mean = 0, sd = 1),
  l3=rnorm(n=25, mean = 10, sd = 1)
)


Then I plot the grouped values. By default the mean function is used to add a summary for the values. However, other functions (e.g. median) can be defined as the FUN parameter.


png(
  "/proj/pehackma/ali/test/test_rnatoolbox/test_groupedScatterPlot_3.png",
  width=500, height=500, pointsize=21)
groupScatterPlot(l=datList, col=rainbow(3),
                 lty=1, lwd=1.5,
                 ylab="Test values")
dev.off()



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I am a Postdoc researcher at the Neuromuscular Disorders Research lab and Genetic Determinants of Osteoporosis Research lab, in University of Helsinki and Folkhälsan RC. I specialize in Bioinformatics. I am interested in Machine learning and multi-omics data analysis. My go-to programming language is R.
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