plotModuleGO: Plot extracted results from module-based GO enrichment...

In DGCA: Differential Gene Correlation Analysis

Plot extracted results from module-based GO enrichment analysis using ggplot2.

Description

Takes a data frame of enrichment results in multiple modules and plots the results. Note that if a GO term enrichment does not exist for that module, it is set as 0 for an OR or 1 for a p-value.

Usage

plotModuleGO(df, nTerms = 5, termVector = NULL, modules = NULL,
  heatmapColor = NULL, plotOR = FALSE, axis_text_col = "black",
  axis_x_text_angle = 45, text_size = 10, guide_title = NULL,
  coord_flip = FALSE, adjust = TRUE)

Arguments

df	The data frame of term enrichments to be plotted.
nTerms	The number of terms for each module whose GO terms with the minimum enrichment p-values for that group should be plotted.
termVector	Optional character vector of GO term strings to plot, overriding other options.
modules	Optional, a list of module names to plot. Optional; if not inputted, all of the module names in the data frame will be used.
heatmapColor	Optional specification of the heatmap colors. If not specified, ?heat.colors will be used.
plotOR	Logical, indicating whether odds ratios should be plotted on the heatmap, instead of -log10 p-values (the default).
axis_text_col	Color of axis text.
axis_x_text_angle	Angle of x-axis text.
text_size	Text size of axes and legend in plot.
guide_title	Optionally, specify the title of legend.
coord_flip	Whether the coordinates should be flipped.
adjust	If p-values are plotted, whether or not the enrichment p-values from each module should be adjusted by the Benjamini-Hochberg method.

Value

A data frame summarizing the GO term enrichments from each group, with columns on the ordered by the minimum p-value for OR term enrichment in any group.

DGCA documentation built on March 31, 2023, 9:22 p.m.