PyBootNet: A Python Package for Bootstrapping and Network Construction

Abstract

PyBootNet is a user-friendly Python package that integrates bootstrapping analysis and correlation network construction. The package offers functions for generating bootstrapped network metrics, statistically comparing network metrics among datasets, and visualizing bootstrapped networks. PyBootNet is designed to be accessible and efficient, with minimal dependencies and straightforward input requirements. To demonstrate its functionality, we applied PyBootNet functions to compare networks within two disparate microbial community datasets: a mouse gut microbiome study and a microbiome study of a built environment. The PyBootNet functions applied include data preprocessing, bootstrapping, correlation matrix calculation, network statistics computation, and network visualization. In both datasets, we show that PyBootNet can generate robust bootstrapped network metrics and identify significant differences in one or more network metrics between pairs of networks. We also show that PyBootNet can create bootstrapped network graphs and identify clusters of nodes that are highly interconnected. We also confirmed its computational efficiency and scalability, which allows it to handle large and complex datasets. PyBootNet provides a powerful and extendible Python bioinformatics solution for bootstrapping analysis and network construction that can be applied to microbial, gene, metabolite and other biological data appropriate for network correlation comparison and analysis.