Statistical Validation with K-Values
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The statistical validation is done by considering the p-values for each linked
node pair in the adjacency network, assuming their neighbors in the bipartite
network are randomly distributed. The FDR and Bonferroni correction for multiple test comparison
are used to correct the p-value in order to take into account the fact that the null random
hypothesis is tested for all the links of the adjacency network and not just once.
The details of the methodology are presented in the following paper:
M. Tumminello, S. Miccichè, F. Lillo, J. Piilo, R. N. Mantegna,
Statistically validated networks in bipartite complex systems,
PLoS ONE, 6 (3), e17994, (2011)
In order to generate the the network projected on one set, this version of the code considers subsets of the other set having degree k.
For further details please refer to the Bacteria/COG bipartite system in the cited paper.
This program takes a bi-partite network in Pajek format (for an example please see pra-qi-5393.net
below) and a boundary value
that indicates how many nodes, counting from the first, belong to the first
set (the boundary value is 5393
in the considered example). The remaining nodes are assumed to belong to the second set.
As output the program gives the following file:
Submit a bipartite network in Pajek .net format to
statistically validate the associated projected networks.
Submit a Network