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Code to calculate a consensus matrix from a set of distance matrices using k-medoids

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Consensus clustering approach to group brain connectivity matrices

Toolbox that calculates the consensus/modularity matrix from a set of distance matrices using k-medoids as described in Consensus clustering approach to group brain connectivity matrices. J.Rasero, Mario Pellicoro, Leonardo Angelini, Jesus M. Cortes, Daniele Marinazzo and Sebastiano Stramaglia. https://doi.org/10.1162/NETN_a_00017.

The folder matlab contains the toolbox in MATLAB. It consists of the function consensus, which calculates the consensus/modularity matrix from a set of distance matrices at different resolutions. Kmedoids function is also included in the MATLAB file version to be add to your path. More details can be found in the documentation attached. It also contains a toy example with the output shown below:

The R version is now also available. It consists of the function consensus and the requirements are the cluster, graphAT and foreach libraries. The requirement of usage of these libraries might change in the future.

Please do not hesitate to contact us for suggestions and remarks to jrasero.daparte@gmail.com

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