pvalEffectPlot: Create an effect size / p-value plot

In tmod: Feature Set Enrichment Analysis for Metabolomics and Transcriptomics

Create an effect size / p-value plot

Description

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

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.

Value

Invisibly returns a NULL value.

tmod documentation built on March 31, 2023, 9 p.m.