KODAMA exploratory analysis in metabolic phenotyping - Zinga, Maria Mgella; Abdel-Shafy, Ebtesam; Melak, Tadele; Vignoli, Alessia; Piazza, Silvano; Zerbini, Luiz Fernando; Tenori, Leonardo; Cacciatore, Stefano (Frontiers in Molecular Biosciences, 2023)
KODAMA is a valuable tool in metabolomics research to perform exploratory analysis. The advanced analytical technologies commonly used for metabolic phenotyping, mass spectrometry, and nuclear magnetic resonance spectroscopy push out a bunch of high-dimensional data. These complex datasets necessitate tailored statistical analysis able to highlight potentially interesting patterns from a noisy background. Hence, the visualization of metabolomics data for exploratory analysis revolves around dimensionality reduction. KODAMA excels at revealing local structures in high-dimensional data, such as metabolomics data. KODAMA has a high capacity to detect different underlying relationships in experimental datasets and correlate extracted features with accompanying metadata. Here, we describe the main application of KODAMA exploratory analysis in metabolomics research.