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Published September 15, 2020 | Version 0.1
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A framework for comparing microbial networks reveals core associations

  • 1. KU Leuven, Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Molecular Bacteriology, Leuven, Belgium
  • 2. KU Leuven, Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Molecular Bacteriology, Leuven, Belgium; VIB-KU Leuven Center for Microbiology, Leuven, Belgium

Description

Microbial network construction and analysis is an important tool in microbial ecology.  As microbial interactions are challenging to infer experimentally, such networks are often constructed from statistically inferred associations and may not represent ecological interactions. Hence, microbial association networks contain a large number of errors and their derived properties do not necessarily reflect true community structure. Such errors can be identified with the use of appropriate null models.

We have developed anuran, a toolbox for investigation of noisy networks with null models, for identification of non-random patterns in groups of association networks. This toolbox compares multiple networks to identify conserved subsets (core association networks, CANs) and other network properties that are shared across all networks. Such groups of networks can be generated from a collection of time series data or from cross-sectional sample sets. We use data from the Global Sponge Project to demonstrate that different orders of sponges have a larger CAN than expected at random. 

This repository contains an archived version of anuran, in addition to all scripts and raw data used for the manuscript.

Notes

The latest version of anuran can be downloaded here: https://github.com/ramellose/anuran This software is also available under an Apache 2.0 license.

Files

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Additional details

Funding

EcoBox – Ecosystem in a box: Dissecting the dynamics of a defined microbial community in vitro 801747
European Commission