reorder.x: logical indicating if the function should reorder the x axis based on clustering
reorder.y: logical indicating if the function should reorder the y axis based on clustering
resort_on_p: logical indicating if the function should reorder x and y axis based on the pvalues of the associations
abs: logical indicating if the function should reorder based the absolute values
cor.abs: logical indicating if the function should reorder the plot base on the absolute values
reorder_dend: Tlogical indicating if the function should reorder the plot based on dendrogram
Returns
heatmap with the results of cor.assoc
Examples
library(stats)#load the datasetm <- as.matrix(synthetic_metabolic_dataset)#Compute the pearson correlation of all the variables in the data.frame metabolic_measurescors<-cor_assoc(m, m, MiMIR::metabolites_subsets$MET63,MiMIR::metabolites_subsets$MET63)#Plot the correlationsplot_corply(cors, main="Correlations metabolites")