marginally significantp < 0.06
Results of correlation analysis were then subject to unsupervised clustering (using the Ward’s method) in order to identify clusters of parameters with similar correlational behavior, which were presented in the form of a correlation matrix (i.e., heatmap). For the sake of increased readability, the heatmap shows only statistically and marginally significant ( p < 0.06) correlations.