A hierarchical method for finding interactions: Jointly using linear correlation and rank correlation analysis
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 do...
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| Format: | Article |
| Language: | English |
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International Academy of Ecology and Environmental Sciences
2015-12-01
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| Series: | Network Biology |
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| Online Access: | http://www.iaees.org/publications/journals/nb/articles/2015-5(4)/a-hierarchical-method-for-finding-interactions.pdf |
| Summary: | 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.
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| ISSN: | 2220-8879 2220-8879 |