| pvalEffectPlot | R Documentation | 
Create a heatmap-like plot showing information about both effect size and p-values.
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
)
| 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 | 
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:
either row / column number or the id of the row / column to plot; NULL if drawing legend
user coordinates of the result to visualize
width and height of the item to plot
Enrichment – a relative value between 0 and 1, where 0 is the minimum and 1 is the maximum enrichment found
P-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.
Invisibly returns a NULL value.
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