Calour: an Interactive, Microbe-Centric Analysis Tool

Area of Science:

• Microbial Ecology
• Bioinformatics
• Data Science

Background:

• Microbiome analyses generate high-dimensional data, posing challenges for interpretation.
• Existing tools often oversimplify data, losing crucial taxonomic details and potentially leading to misleading visualizations.
• A need exists for methods that offer detailed exploration at multiple resolutions.

Purpose of the Study:

• To introduce Calour, a user-friendly tool for interactive microbiome data exploration.
• To provide a study-centric data model for managing sample-by-feature tables and metadata.
• To enable visualization and exploration of microbial patterns using integrated knowledge databases.

Main Methods:

• Developed a user-friendly, study-centric data model for microbiome data.
• Implemented an interactive heatmap for data visualization.
• Integrated microbial knowledge databases and statistical tools for enhanced exploration.
• Applied Calour to diverse public microbiome datasets (e.g., gut, skin, metabolomics).

Main Results:

• Calour effectively visualizes microbial patterns in complex datasets.
• The tool facilitated the discovery of novel microbial patterns and potential contaminants.
• Demonstrated utility across various microbiome studies, including animal models and human data.
• Revealed previously obscured microbial subgroups and their associations.

Conclusions:

• Calour offers a powerful approach for interactive microbiome data exploration.
• It aids in generating novel biological hypotheses by integrating data visualization with annotation databases.
• Calour serves as an effective first-step tool for uncovering patterns in microbiome research.