EasyMap - An Interactive Web Tool for Evaluating and Comparing Associations of Clinical Variables and Microbiome...

Area of Science:

• Microbiome research
• Bioinformatics
• Statistical modeling

Background:

• Comparing microbial profiles across human groups is crucial in microbiome studies.
• Multivariate linear regression is commonly used but selecting appropriate metadata variables is challenging due to correlations.

Purpose of the Study:

• To introduce EasyMap, an interactive online tool for running, visualizing, and comparing multiple multivariate linear regression models.
• To facilitate the identification of critical metadata variables and selection of optimal models in microbiome data analysis.

Main Methods:

• EasyMap allows running multiple multivariate linear regression models on the same features and metadata.
• It provides side-by-side visualization of association results across models, enabling evaluation of metadata variable impact.
• Users can filter associations by significance, focus on specific microbes, and identify robust associations across models.

Main Results:

• EasyMap offers an intuitive interface for comparing various models to pinpoint robust microbial feature associations.
• The tool effectively handles microbiome data and other tabular data with numeric features and metadata.
• It aids in understanding the influence of different metadata variables on microbial associations.

Conclusions:

• EasyMap enhances the process of multivariate linear regression for microbiome analysis.
• The tool simplifies the identification of significant microbial associations and aids in model selection.
• EasyMap is a valuable resource for researchers in microbiome and other data analysis fields.