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I used different algorithms for splitting my large gene network into different sub-networks using Cytoscape. I compared the modularity scores and decided that the algorithm with the best modularity score will be used for clustering the network.

My colleague came up with the argument that modularity scores can only be compared for different number of clusters being created by the same algorithm.

So, my question is if modularity scores can be used to compare between different algorithms or only in the case of the same algorithm producing different number of clusters.

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  • $\begingroup$ If you don't get an answer here, you might do better to transfer your question (delete and repost) to SE Bioinformatics, which would seem more appropriate. $\endgroup$ – David Dec 31 '18 at 9:33
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Since the goal of modularity estimation algorithms is to find the community structure that maximizes modularity, it is valid to compare different algorithms based on their modularity estimate. However, i) it is not the only consideration for choosing a community detection algorithm, and ii) the obtained modularity estimate will depend on the particular structure of each network, e.g. its number of nodes. For a principled comparison between several different algorithms, see Yang et al. (2016). Based on multiple criteria, they identify the multilevel (or Louvain) algorithm (Blondel et al. 2008) as the overall best choice.


References
- Yang, Zhao, René Algesheimer, and Claudio J. Tessone. “A Comparative Analysis of Community Detection Algorithms on Artificial Networks.” Scientific Reports 6, no. 1 (August 2016). https://doi.org/10.1038/srep30750.
- Blondel, Vincent D., Jean-Loup Guillaume, Renaud Lambiotte, and Etienne Lefebvre. “Fast Unfolding of Communities in Large Networks.” Journal of Statistical Mechanics: Theory and Experiment 2008, no. 10 (October 2008): P10008. https://doi.org/10.1088/1742-5468/2008/10/P10008.

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