C3NA: correlation and consensus-based cross-taxonomy network analysis for compositional microbial data

• Published in: BMC bioinformatics Vol. 23; no. 1; pp. 1 - 16
• Main Authors: Song, Kuncheng, Zhou, Yi-Hui
• Format: Journal Article
• Language: English
• Published: London BioMed Central Ltd 08.11.2022; BioMed Central; BMC
• Subjects: Abundance; Analysis; Annotations; Co-occurrence network analysis; Colorectal cancer; Colorectal carcinoma; Computer graphics; Consensus clustering; Correlation analysis; Crohn's disease; Data processing; Datasets; Disease control; Graphical user interface; Information management; Interfaces; Methods; Microbiome; Microbiota (Symbiotic organisms); Microorganisms; Module preservation analysis; Network analysis; Phylogeny; R package; Taxa; Taxonomy; United States

Studying the co-occurrence network structure of microbial samples is one of the critical approaches to understanding the perplexing and delicate relationship between the microbe, host, and diseases. It is also critical to develop a tool for investigating co-occurrence networks and differential abund...