Figure 1: Overview of transkingdom network analysis.
Omics data for multiple data types (e.g. microbial, gene expression, etc.) are analyzed to identify differentially abundant elements (e.g. microbes, genes, etc.). For each group (e.g. treatment or control) co-expression networks are constructed for each data type followed by the identification of dense sub-networks (modules). Calculating correlations between module elements of the different data types creates the “transkingdom” network. Network interrogation of the transkingdom network allows identification of causal members and regulatory relationships.