ddplot: Create a heatmap showing the correlations in two conditions.

In DGCA: Differential Gene Correlation Analysis

Create a heatmap showing the correlations in two conditions.

Description

This function orders the differences in correlations between conditions by the median strength of correlation differences for each gene and plots a heatmap of the correlations in each condition (lower = condition A, upper = condition B) using the heatmap.2 function from the gplots package.

Usage

ddplot(dcObject = NULL, corMatA = NULL, corMatB = NULL, zDiff = NULL,
  flip = TRUE, color_palette = NULL, customize_heatmap = FALSE,
  heatmapClassic = FALSE, corPower = 2, ...)

Arguments

dcObject	A differential correlation object from which correlation and differential correlation matrices will be extracted. Optional; can also input the correlation matrices and differential correlation matrix individually.
corMatA	Optional, correlation matrix from condition A. Will be plotted in the lower left triangle.
corMatB	Optional, correlation matrix from condition B. Will be plotted in the upper right triangle.
zDiff	Optional, difference measure of correlations between conditions A and B.
flip	Switch the ordering of z-differences to be inverse. Default = TRUE
color_palette	Colors for plotting the heatmap. If not specified, defaults to a color-blind palette where blue corresponds to a negative correlation and orange/red corresponds to a positive one.
customize_heatmap	Option to remove some default options in the heatmap plot, to allow users to add custom options.
heatmapClassic	Option to make the heatmap more granular (e.g., not showing the individual gene symbols) and more of a "classic" type of heatmap. Overrides most other heatmap options.
corPower	The power to raise the correlations to before plotting the classic heatmap. Larger correlation powers emphasize larger correlation values relatively more compared to smaller correlation values.
...	Additional plotting arguments to the heatmap.2 function.

Value

The sorted difference in z-score matrix in both conditions, which you can use to create your own plot if you'd prefer.

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