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A-SIMA/A-MAP: a comprehensive toolkit for NMR-based metabolomics analysis
Abigail Chiu1, Mehdi Rahimi1, Woonghee Lee2
1Department of Chemistry, University of Colorado Denver, Denver, CO, 80204, USA.
Introduction:
Metabolomics is the comprehensive study of small molecules in biological systems. It has recently garnered attention for its wide variety of applications such as diseases, drug treatments, agriculture, and more. As the interest in metabolomics grow, meeting the demands of cutting-edge research requires software tools that not only advance analytical capabilities, but also prioritize user-friendly features.
Objectives:
In response to this need, we present two new computer programs, A-SIMA: Advanced-Software for Interactive Metabolite Analysis and A-MAP: A Multivariate Analysis Program. These tools aim to introduce new capabilities for metabolite identification and data analysis, and thereby advancing the computational methodology in NMR-based metabolomics.
Methods:
A-SIMA is designed with an easy-to-use graphical user interface which allows users to perform metabolite identification on 1D and 2D NMR data effortlessly with complete control over the identification process. Similarly, A-MAP facilitates multivariate statistical analysis of metabolite data through a straightforward process. It offers analysis options such as Principal Component Analysis and Orthogonal Partial Least Squares-Discriminant Analysis using regions of interests as inputs.
Results:
Both A-SIMA and A-MAP are pre-built in the POKY suite, available at https://poky.clas.ucdenver.edu , with tutorial videos on YouTube for guidance on not only the programs, but also installation. The POKY suite is a software program for NMR biomolecular analysis. With the addition of these programs in POKY, researchers and professionals can experience a fully integrated process for every step of their metabolite analysis. Data can also be easily exported from these programs to be applied elsewhere.
Conclusion:
The introduction of A-SIMA and A-MAP can be promising tools that can lead significant advancements in metabolomics research. These tools offer enhanced capabilities for metabolite analysis and statistical modelling in a user-friendly manner. Their integration into the POKY suite ensures accessibility, usability, and efficiency.
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