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Showing content from https://cran.r-project.org/web/packages/fda.usc/../rmarkdown/../sinaplot/vignettes/SinaPlot.html below:

sinaplot: an enhanced chart for simple and truthful representation of single observations over multiple classes

x <- c(rnorm(200, 4, 1), rnorm(200, 5, 2), rnorm(400, 6, 1.5))
groups <- c(rep("Cond1", 200), rep("Cond2", 200), rep("Cond3", 400))

library(sinaplot)

#Use any "plot" argument
sinaplot(x, groups, col = 2:4, pch = 20, bty = "n")

We use a cohort of 2095 AML, ALL and healthy bone marrow samples to illustrate some of the strengths of sinaplot.

sinaplot(Gene ~ Class, data = blood, pch = 20)

By setting the argument scale = FALSE we turn off the group-wise scaling based on the class with the highest density.

sinaplot(Gene ~ Class, data = blood, pch = 20, scale = FALSE)

Using the method = "counts" to compute the borders we get a less smooth spread of the samples due to the absence of the kernel density estimate.

sinaplot(Gene ~ Class, data = blood, pch = 20, scale = FALSE, method = "counts")

Sinaplot aesthetics can be tweaked in the same manner as in graphics::plot.

par(mar = c(9,4,4,2) + 0.1)
n_groups <- length(levels(blood$Class))

sinaplot(Gene ~ Class, data = blood, pch = 20, xaxt = "n", col = rainbow(n_groups), 
         ann = FALSE, bty = "n")
axis(1, at = 1:n_groups, labels = FALSE)
text(x = 1:n_groups,
     y = par()$usr[3] - 0.1 * (par()$usr[4] - par()$usr[3]),
     labels = levels(blood$Class), srt = 45, xpd = TRUE, adj = 1,
     cex = .8)

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