A hierarchical method for finding interactions: Jointly using linear correlation and rank correlation analysis

• Main Author: WenJun Zhang
• Format: Article
• Language: English
• Published: International Academy of Ecology and Environmental Sciences 2015-12-01
• Series: Network Biology
• Subjects: partial correlation; correlation measure; Pearson linear correlation; Spearman rank correlation; algorithm; set operation; statistic test; interaction finding
• Online Access: http://www.iaees.org/publications/journals/nb/articles/2015-5(4)/a-hierarchical-method-for-finding-interactions.pdf

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.