MANTA, an integrative database and analysis platform that relates microbiome and phenotypic data.

Area of Science:

• Microbiology
• Bioinformatics
• Computational Biology

Background:

• Growing interest in host-microbiota interactions necessitates advanced analytical tools.
• Existing tools primarily focus on taxonomic profiling, lacking robust correlation with host phenotypic data.

Purpose of the Study:

• To develop MANTA (Microbiota And pheNoType correlation Analysis platform), a web-based integrative database and analysis tool.
• To enable correlation of microbial composition with host phenotypic parameters through an intuitive interface.

Main Methods:

• Development of a web-based integrative database and analysis platform (MANTA).
• Implementation of an intuitive user interface for correlating microbial and phenotypic data.
• Utilizing a case study to demonstrate the platform's capabilities.

Main Results:

• MANTA successfully integrates and analyzes host-microbiota data.
• The platform efficiently identifies significant correlations between microbial abundances and host phenotypes.
• Case study validated MANTA's ability to support findings from previous studies.

Conclusions:

• MANTA provides a valuable tool for exploring microbiota-phenotype relationships.
• The platform facilitates interpretation of complex host-microbiota interactions.
• MANTA is accessible for download, promoting wider research application.