Gaussian copula correlation network inference

This application enables the user to perform network inference on heterogeneous variables by assuming a Gaussian copula structure. Even if the data set is high dimensional, the computational cost is reduced by using a pairwise likelihood. The calculations are performed via the heterocop R package.

Dataset

Display only a subset of your data

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Columns

from

Rows

from

Download the selected dataset

Correlation matrix

Display only a subset of your correlation matrix

Which rows and columns do you want to display?

Columns

from

Rows

from

Download the correlation matrix of the copula

Corrplot

Customize your corrplot

Download the corrplot

Graphical representation

The graph corresponding to the correlation matrix is shown below. An edge is present between two vertices if their correlation coefficient is greater than the threshold defined below. The colors correspond to the variable type (discrete or continuous), but more coloring options are available in the Customize your graph section.

Enter the correlation threshold

Customize your graph

Select the color for continuous variables

Select the color for discrete variables

I want to add more groups of variables

Enter the number of groups

Download the graph