ddplot {DGCA} | R Documentation |
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.