Welcome to the bngal wiki!

What is bngal?

Biological Network Graph Analysis and Learning (bngal) is a package written in R to create high-quality, complex correlation networks from microbial abundance data.

bngal can create correlation networks at each level of taxonomic classification (phylum to ASV) from a taxonomic count table to visualize complex co-occurrence substructures in the data via edge betweenness clustering. Numeric variables from a corresponding metadata table can be optionally included to explore environmental-taxonomic correlations. “Subcommunity networks” can also be created in parallel to explore different correlation patterns within a dataset in addition to a global comparison. For example, one may want to examine separate networks for the human skin, oral, and gut microbiomes from the same dataset, while also examining microbial co-occurrence patterns across the entire body. Another may want to do the same thing for subsurface environments that span distinct geological contexts. As such, microbial ecologists from a wide range of backgrounds may be interested in applying bngal to model microbial niche space in the habitats they study with network analysis!

Visit the Quick Start Guide for examples on how to use bngal.

If you found bngal helpful for your research, please consider citing our paper that first used this tool.

Contact bngal.help@gmail.com with any questions, or open a GitHub issue if you have trouble with the software.

A huge thanks goes to Prof. Maggie Osburn and Dr. Caitlin Casar for their invaluable advice on the theory behind and implementation of bngal!

bngal developer: Dr. Matt Selensky