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Create an effect size / p-value plot

pvalEffectPlot.Rd

Create a heatmap-like plot showing information about both effect size and p-values.

Usage

pvalEffectPlot(
  e,
  p,
  pval.thr = 0.01,
  pval.cutoff = 1e-06,
  row.labels = NULL,
  col.labels = NULL,
  plot.func = NULL,
  grid = "at",
  grid.color = "#33333333",
  plot.cex = 1,
  text.cex = 1,
  col.labels.style = "top",
  symmetrical = FALSE,
  legend.style = "auto",
  min.e = NULL,
  max.e = NULL
)

Arguments

e

matrix with effect sizes

p

matrix with probabilities

pval.thr

The p-value must be this or lower in order for a test result to be visualized

pval.cutoff

On visual scale, all p-values below pval.cutoff will be replaced by pval.cutoff

row.labels

Labels for the modules. This must be a named vector, with module IDs as vector names. If NULL, module titles from the analyses results will be used.

col.labels

Labels for the columns. If NULL, names of the elements of the list x will be used.

plot.func

Optionally, a function to be used to draw the dots. See "Details"

grid

Style of a light-grey grid to be plotted; can be "none", "at" and "between"

grid.color

Color of the grid to be plotted (default: light grey)

plot.cex

a numerical value giving the amount by which the plot symbols will be maginfied

text.cex

a numerical value giving the amount by which the plot text will be magnified, or a vector containing three cex values for row labels, column labels and legend, respectively

col.labels.style

Style of column names: "top" (default), "bottom", "both", "none"

symmetrical

effect sizes are distributed symmetrically around 0 (default: FALSE)

legend.style

Style of the legend: "auto" -- automatic; "broad": pval legend side by side with effect size legend; "tall": effect size legend above pval legend; "none" -- no legend.

min.e, max.e

scale limits for the effect size

Value

Invisibly returns a NULL value.

Details

pvalEffectPlot shows a heatmap-like plot. Each row corresponds to one series of tests (e.g. one module), and each column corresponds to the time points or conditions for which a given analysis was run. Each significant result is shown as a red dot. Size of the dot corresponds to the effect size (or any arbitrary value), and intensity of the color corresponds to the log10 of p-value.

Just like a heatmap corresponds to a single numeric matrix, the pvalue / effect plot corresponds to two matrices: one with the effect size, and another one with the p-values. Each cell in the matrix corresponds to the results of a single statistical test.

For example, a number of genes or transcriptional modules might be tested for differential expression or enrichment, respectively, in several conditions.

By default, each test outcome is represented by a dot of varying size and color. Alternatively, a function may be specified with the parameter 'plot.func'. It will be called for each test result to be drawn. The plot.func function must take the following arguments:

  • row, coleither row / column number or the id of the row / column to plot; NULL if drawing legend

  • x, yuser coordinates of the result to visualize

  • w, hwidth and height of the item to plot

  • eEnrichment -- a relative value between 0 and 1, where 0 is the minimum and 1 is the maximum enrichment found

  • pP-value -- an absolute value between 0 and 1

For the purposes of drawing a legend, the function must accept NULL p-value or a NULL enrichment parameter.