EpiMetal: an open-source graphical web browser tool for easy statistical analyses in epidemiology and metabolomics

Area of Science:

• Computational biology
• Epidemiology
• Bioinformatics

Background:

• Statistical analysis of large datasets in epidemiology and metabolomics often requires specialized programming skills.
• Existing tools may lack intuitive interfaces or the flexibility to handle diverse data types.

Purpose of the Study:

• To develop an accessible, user-friendly web application for statistical analysis and visualization of extensive epidemiological and metabolic data.
• To enable researchers without prior programming or statistical software knowledge to perform complex data analyses.

Main Methods:

• Development of EpiMetal, a single-page JavaScript web application.
• Integration of standard epidemiological analyses and self-organizing maps for metabolic profiling.
• Support for multiple extensive datasets with continuous and categorical variables.

Main Results:

• EpiMetal provides an intuitive graphical interface for statistical analyses and data visualization.
• The application successfully handles extensive datasets, including pilot data with over 500 molecular measures and large cohorts exceeding 10,000 samples.
• Analyses can be saved and shared via a web link.

Conclusions:

• EpiMetal democratizes advanced statistical analysis in epidemiology and metabolomics.
• The tool empowers researchers to derive data-driven insights from complex datasets without specialized technical expertise.
• Open access availability promotes wider adoption and collaboration in the scientific community.