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Because of the importance of systems-level interpretation, many methods have been developed to identify biologically significant pathways using metabolomics data. In this review, we first describe a complete metabolomics workflow (sample preparation, data acquisition, pre-processing, downstream analysis, etc.). We then comprehensively review 24 approaches capable of performing functional analysis, including those that combine metabolomics data with other types of data to investigate the disease-relevant changes at multiple omics layers. We discuss their availability, implementation, capability for pre-processing and quality control, supported omics types, embedded databases, pathway analysis methodologies, and integration techniques. We also provide a rating and evaluation of each software, focusing on their key technique, software accessibility, documentation, and user-friendliness. Following our guideline, life scientists can easily choose a suitable method depending on method rating, available data, input format, and method category. More importantly, we highlight outstanding challenges and potential solutions that need to be addressed by future research. To further assist users in executing the reviewed methods, we provide wrappers of the software packages at https:\/\/github.com\/tinnlab\/metabolite-pathway-review-docker.<\/jats:p>","DOI":"10.1093\/bib\/bbae498","type":"journal-article","created":{"date-parts":[[2024,10,14]],"date-time":"2024-10-14T06:06:55Z","timestamp":1728886015000},"source":"Crossref","is-referenced-by-count":21,"title":["Current approaches and outstanding challenges of functional annotation of metabolites: a comprehensive review"],"prefix":"10.1093","volume":"25","author":[{"given":"Quang-Huy","family":"Nguyen","sequence":"first","affiliation":[{"name":"Department of Computer Science and Software Engineering, Auburn University , Auburn, AL 36849,","place":["United States"]}]},{"given":"Ha","family":"Nguyen","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Software Engineering, Auburn University , Auburn, AL 36849,","place":["United States"]}]},{"given":"Edwin C","family":"Oh","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine, UNLV School of Medicine, University of Nevada , Las Vegas, NV 89154,","place":["United States"]}]},{"given":"Tin","family":"Nguyen","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Software Engineering, Auburn University , Auburn, AL 36849,","place":["United States"]}]}],"member":"286","published-online":{"date-parts":[[2024,10,13]]},"reference":[{"key":"2024101406063631000_ref1","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1038\/s43856-022-00208-2","article-title":"Adiposity and NMR-measured lipid and metabolic biomarkers among 30,000 Mexican adults","volume":"2","author":"Aguilar-Ramirez","year":"2022","journal-title":"Commun Med"},{"key":"2024101406063631000_ref2","doi-asserted-by":"publisher","first-page":"272","DOI":"10.1016\/j.atherosclerosis.2015.03.034","article-title":"Associations of multiple lipoprotein and apolipoprotein measures 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