Heatmap of differentially expressed proteinsSource:
This function generates a heatmap to visualize differentially expressed proteins between groups
heatmap_de( fit_df, df, adj_method = "BH", cutoff = 0.05, lfc = 1, sig = "adjP", n_top = 20, palette = "viridis", text_size = 10, save = FALSE, file_path = NULL, file_name = "HeatmapDE", file_type = "pdf", dpi = 80, plot_height = 7, plot_width = 7 )
fit_dfobject from performing
norm_dfobject or the
imp_dfobject from which the
fit_dfobject was obtained.
Method used for adjusting the p-values for multiple testing. Default is
Cutoff value for p-values and adjusted p-values. Default is 0.05.
Minimum absolute log2-fold change to use as threshold for differential expression. Default is 1.
Criteria to denote significance. Choices are
"adjP"(default) for adjusted p-value or
Number of top hits to include in the heat map.
Viridis color palette option for plots. Default is
viridisfor available options.
Text size for axis text, labels etc.
TRUEsaves a copy of the plot in the directory provided in
A string containing the directory path to save the file.
File name to save the plot. Default is "HeatmapDE."
File type to save the plot. Default is
Plot resolution. Default is
Height of the plot. Default is 7.
Width of the plot. Default is 7.
By default the tiles in the heatmap are reordered by intensity values along both axes (x axis = samples, y axis = proteins).
## Build a heatmap of differentially expressed proteins using the provided ## example fit_df and norm_df data objects heatmap_de(covid_fit_df, covid_norm_df) ## Create a heatmap with P-value of 0.05 and log fold change of 1 as ## significance criteria. heatmap_de(covid_fit_df, covid_norm_df, cutoff = 0.05, sig = "P") ## Visualize the top 30 differentially expressed proteins in the heatmap and ## change the color palette heatmap_de(covid_fit_df, covid_norm_df, cutoff = 0.05, sig = "P", n_top = 30, palette = "magma" )