Interaction redundancy

Interaction redundancy was proposed to describe the conserved functional roles of microbial interactions within a community. We provided AURORA (quAntify the redUndancy in micRObial inteRactions using pArtial information decomposition) package here to quantify the interaction redundancy within a microbial community from microbial abundance data.

AURORA package

Prerequisite

The package was written in Python3. Following Python packages should be installed:

• numpy 2.1.3
• pandas 2.2.3

Install

git clone https://github.com/deepomicslab/Interaction-redundancy.git

Usage

python interaction_redundancy_cal.py  --ICN_ref ref_ICN.csv --abundance_file example_data/abundance_example.tsv

Parameters are shown bellow:

• --ICN_ref: The reference interaction content network file (OTU interaction x KEGG interaction).
• --abundance_file: The taxon abundance data (OTU x sample).
• --output_file: The output file (default: IR_output.txt).
• --distance_measure: The distance measures used for calculating interaction redundancy, including weighted_jaccard_distance, euclidean_distance, correlation_distance, and manhattan_distance (default: weighted_jaccard_distance).

For more information, please use python interaction_redundancy_cal.py -h.

Output

Each row in the output file represents a sample, with the first column displaying the interaction redundancy value and the second column displaying the interaction diversity value.

Maintainer

Ruo Han Wang ruohawang2-c@my.cityu.edu.hk