Generate multidimensional scaling (MDS) plots to explore miRNA/gene expression distances

This function performs multidimensional scaling in order to produce a simple scatterplot that shows miRNA/gene expression variations among samples. In particular, starting from a MirnaExperiment object, this functions allows to visualize both miRNA and gene expression in the multidimensional space. Moreover, it is possible to color samples on the basis of specific variables, and this is extremely useful to assess miRNA/gene expression variations between distinct biological groups.

Usage

plotDimensions(
  mirnaObj,
  assay,
  condition = NULL,
  dimensions = c(1, 2),
  labels = FALSE,
  boxedLabel = TRUE,
  pointSize = 3,
  pointAlpha = 1,
  colorScale = NULL,
  title = NULL,
  fontSize = 12,
  fontFamily = "",
  legend = "top",
  borderWidth = 1,
  allBorders = TRUE,
  grid = FALSE,
  ...
)

Arguments

mirnaObj: A MirnaExperiment object containing miRNA and gene data
assay: The results to display. It must be either 'microRNA', to plot miRNA expression, or 'genes', to produce MDS plot for genes
condition: It must be the column name of a variable specified in the metadata (colData) of a MirnaExperiment object; or, alternatively, it must be a character/factor object that specifies group memberships (eg. c("healthy, "healthy", "disease", "disease"))
dimensions: It is a numeric vector of length 2 that indicates the two dimensions to represent on the plot. Default is c(1, 2) to plot the two dimensions that account for the highest portion of variability
labels: Logical, whether to display labels or not. Default is FALSE
boxedLabel: Logical, whether to show labels inside a rectangular shape (default) or just as text elements
pointSize: The size of points in the MDS plot (default is 3)
pointAlpha: The transparency of points in the MDS plot (default is 1)
colorScale: It must be a named character vector where values correspond to R colors, while names coincide with the groups specified in the condition parameter (eg. c("healthy" = "green", "disease" = "red")). Default is NULL, in order to use the default color scale. Available color formats include color names, such as 'blue' and 'red', and hexadecimal colors specified as #RRGGBB
title: The title of the plot. Default is NULL not to include a plot title
fontSize: The base size for text elements within the plot. Default is 12
fontFamily: The base family for text elements within the plot
legend: The position of the legend. Allowed values are top, bottom, right, left and none. The default setting is top to show a legend above the plot. If none is specified, the legend will not be included in the graph.
borderWidth: The width of plot borders (default is 1)
allBorders: Logical, whetether to show all panel borders, or just the bottom and left borders. Default is TRUE
grid: Logical, whether to show grid lines or not. Default is FALSE
...: Other parameters that can be passed to limma::plotMDS() function

Value

An object of class ggplot containing the plot.

Note

To perform multidimensional scaling, this function internally uses limma::plotMDS() function provided by limma package.

References

Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, Smyth GK (2015). “limma powers differential expression analyses for RNA-sequencing and microarray studies.” Nucleic Acids Research, 43(7), e47. doi:10.1093/nar/gkv007.

Author

Jacopo Ronchi, jacopo.ronchi@unimib.it

Examples

# load example MirnaExperiment object
obj <- loadExamples()

# produce MDS plot for genes with condition color
plotDimensions(obj, "genes", condition = "disease")