Repository:CAnBioNet/TkNA Tag:v1.2.1 Released by:macovskym
This work was done as a collaboration between Oregon State University and NCI/NIH. Kindly cite the following paper if you use TkNA:
Newman, N.K., Macovsky, M.S., Rodrigues, R.R. et al. Transkingdom Network Analysis (TkNA): a systems framework for inferring causal factors underlying host–microbiota and other multi-omic interactions. Nat Protoc (2024). Nature.com/articles/TkNA
This code performs various tasks related to network reconstruction and analysis, as well as network visualization. It was designed for analyzing microbiome and phenotype data, and the code is organized into five main sections:
1. Network reconstruction: This section reconstructs a network from input data using intake_data.py, run.py, and to_csv.py scripts.
2. Network quality assessment: This section assesses the quality of the reconstructed network using the assess_network.py script.
3. Network analysis: This section analyzes the network, and involves an optional step of generating partitions using either the Louvain algorithm or Infomap, followed by the calculation of network, subnetwork, and node properties using the calc_network_properties.py script.
4. Random network creation and analysis: This section creates random networks and analyzes them to compare their properties to the reconstructed network using create_random_networks.py, compute_network_stats.py, and synthesize_network_stats.py scripts.
5. Network visualization: This section visualizes the network using dot_plots.py, plot_abundance.py, and plot_density.py scripts.