Description Usage Arguments Author(s) References Examples
This function calculates correlation between modules (sub-communities) and environmental variables. The most connected node(taxon) in a given module is considered a good representation of the module. This is implemented in accordance to (Deng et al. 2012) where correlations between module-based eigengenes and environmental factors are used to detect the modules' response to environmental change.
1 | module_env_correlation(co_occur_res, select.variables = NULL, ...)
|
co_occur_res |
an object returned by 'co_occurence_network' function. |
select.variables |
environmental variables of interest. |
Alfred Ssekagiri assekagiri@gmail.com, Umer Zeeshan Ijaz Umer.Ijaz@glasgow.ac.uk
http://userweb.eng.gla.ac.uk/umer.ijaz/, Umer Ijaz, 2015
Deng, Ye, Yi-Huei Jiang, Yunfeng Yang, Zhili He, Feng Luo, and Jizhong Zhou. 2012. “Molecular Ecological Network Analyses.” BMC Bioinformatics 13 (1). BioMed Central: 113.
1 2 3 | mod.env.cor <- module_env_correlation(co_occur)
p <- plot_taxa_env(mod.env.cor)
print(p)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.