Network Biology, 2015, 5(4): 137-145
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A hierarchical method for finding interactions: Jointly using linear correlation and rank correlation analysis

WenJun Zhang
School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China; International Academy of Ecology and Environmental Sciences, Hong Kong

Received 20 October 2015;Accepted 5 November 2015;Published online 1 December 2015

In the earlier studies, I pointed out that a network changed in a local domain can be approximated as a linear network, i.e., all between-node (or -taxon, -component, etc) changes in the local domain are treated as linear ones and Pearson linear correlation measure can be used. For a little wider domain, the quasi-linear measure, Spearman rank correlation can be used also. In present study, I jointly use Pearson linear correlation measure and Spearman rank correlation measure and their partial correlations to find interactions. First, I define some hierarchical principles for finding interactions. Reliability levels are then defined using set operations. The full algorithm and Matlab codes for finding interactions are given.

Keywords partial correlation;correlation measure;Pearson linear correlation;Spearman rank correlation;algorithm;set operation;statistic test;interaction finding.

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