visualize_correlations {CINNA}

Correlation plot between centrality measures

Description

This function draw correlation plot between pair of centrality measures

Usage

visualize_correlations(x, scale = TRUE, method = "pearson")

Arguments

x

a list indicating calculated centrality measures

scale

Whether the centrality values should be scaled or not(default=TRUE)

method

a character string describing the type of correlation coefficient (or covariance) to be computed. The proper values are "pearson", "kendall", or "spearman". (default="pearson")

Details

This function illustrates pairwise correlation plot of computed centrality measures. The names of centralities shown in the result plot is abbreviated and compelete names can be seen in "proper_centralities" function. Colors from red to blue indicate the intensity of correlation value. If two centrality measures have an inverse relationship then their correspnding color in plot have to be red and vice versa.

Value

The function generates a correlation plot between pairs of centrality measures. The function takes a list x as input, which contains the computed centrality measures. If the scale parameter is set to TRUE, the centrality values will be scaled before computing the correlations. The method parameter specifies the type of correlation coefficient to be computed: "pearson" (default), "kendall", or "spearman". The function creates a pairwise correlation plot, where each cell represents the correlation between a pair of centrality measures. The color of each cell indicates the strength and direction of the correlation, ranging from red (negative correlation) to blue (positive correlation). The function returns the pairwise correlation plot.

Author(s)

Minoo Ashtiani, Mehdi Mirzaie, Mohieddin Jafari

See Also

ggpairs