Current approaches and outstanding challenges of functional annotation of metabolites: a comprehensive review.

IF 6.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Quang-Huy Nguyen, Ha Nguyen, Edwin C Oh, Tin Nguyen
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引用次数: 0

Abstract

Metabolite profiling is a powerful approach for the clinical diagnosis of complex diseases, ranging from cardiometabolic diseases, cancer, and cognitive disorders to respiratory pathologies and conditions that involve dysregulated metabolism. 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.

代谢物功能注释的当前方法和突出挑战:全面综述。
代谢组学分析是临床诊断复杂疾病的有力方法,其范围从心脏代谢疾病、癌症和认知障碍到呼吸系统病症和涉及代谢失调的疾病。由于系统级解读的重要性,人们开发了许多方法来利用代谢组学数据识别具有生物学意义的通路。在本综述中,我们首先介绍了完整的代谢组学工作流程(样品制备、数据采集、预处理、下游分析等)。然后,我们全面回顾了能够进行功能分析的 24 种方法,包括那些将代谢组学数据与其他类型的数据相结合,在多个 omics 层面研究疾病相关变化的方法。我们讨论了这些方法的可用性、实施情况、预处理和质量控制能力、支持的 omics 类型、嵌入式数据库、通路分析方法和集成技术。我们还对每种软件进行了评级和评估,重点关注其关键技术、软件可访问性、文档和用户友好性。根据我们的指南,生命科学家可以很容易地根据方法评级、可用数据、输入格式和方法类别选择合适的方法。更重要的是,我们强调了未来研究需要解决的突出挑战和潜在解决方案。为了进一步帮助用户执行所审查的方法,我们在 https://github.com/tinnlab/metabolite-pathway-review-docker 网站上提供了软件包的封装程序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Briefings in bioinformatics
Briefings in bioinformatics 生物-生化研究方法
CiteScore
13.20
自引率
13.70%
发文量
549
审稿时长
6 months
期刊介绍: Briefings in Bioinformatics is an international journal serving as a platform for researchers and educators in the life sciences. It also appeals to mathematicians, statisticians, and computer scientists applying their expertise to biological challenges. The journal focuses on reviews tailored for users of databases and analytical tools in contemporary genetics, molecular and systems biology. It stands out by offering practical assistance and guidance to non-specialists in computerized methodologies. Covering a wide range from introductory concepts to specific protocols and analyses, the papers address bacterial, plant, fungal, animal, and human data. The journal's detailed subject areas include genetic studies of phenotypes and genotypes, mapping, DNA sequencing, expression profiling, gene expression studies, microarrays, alignment methods, protein profiles and HMMs, lipids, metabolic and signaling pathways, structure determination and function prediction, phylogenetic studies, and education and training.
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