A Review of Web-Based Metagenomics Platforms for Analysing Next-Generation Sequence Data

IF 2.1 4区生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY

Biochemical Genetics Pub Date : 2023-07-28 DOI:10.1007/s10528-023-10467-w

Arunmozhi Bharathi Achudhan, Priya Kannan, Annapurna Gupta, Lilly M. Saleena

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引用次数: 0

Abstract

Metagenomics has now evolved as a promising technology for understanding the microbial population in the environment. By metagenomics, a number of extreme and complex environment has been explored for their microbial population. Using this technology, researchers have brought out novel genes and their potential characteristics, which have robust applications in food, pharmaceutical, scientific research, and other biotechnological fields. A sequencing platform can provide a sequence of microbial populations in any given environment. The sequence needs to be analysed computationally to derive meaningful information. It is presumed that only bioinformaticians with extensive computational skills can process the sequencing data till the downstream end. However, numerous open-source software and online servers are available to analyse the metagenomic data developed for a biologist with less computational skills. This review is focused on bioinformatics tools such as Galaxy, CSI-NGS portal, ANASTASIA and SHAMAN, EBI- metagenomics, IDseq, and MG-RAST for analysing metagenomic data.

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分析下一代序列数据的基于网络的元基因组学平台综述。

目前，元基因组学已发展成为了解环境中微生物种群的一项前景广阔的技术。通过元基因组学，人们探索了许多极端复杂环境中的微生物种群。利用这项技术，研究人员发现了新基因及其潜在特征，并将其广泛应用于食品、制药、科学研究和其他生物技术领域。测序平台可以提供任何特定环境中微生物种群的序列。要获得有意义的信息，需要对序列进行计算分析。一般认为，只有具备丰富计算技能的生物信息学家才能处理测序数据，直至下游。然而，许多开源软件和在线服务器可用于分析为计算技能较低的生物学家开发的元基因组数据。本综述主要介绍用于分析元基因组数据的生物信息学工具，如 Galaxy、CSI-NGS 门户网站、ANASTASIA 和 SHAMAN、EBI-元基因组学、IDseq 和 MG-RAST。

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

Biochemical Genetics 生物-生化与分子生物学

CiteScore

3.90

自引率

0.00%

发文量

133

审稿时长

4.8 months

期刊介绍： Biochemical Genetics welcomes original manuscripts that address and test clear scientific hypotheses, are directed to a broad scientific audience, and clearly contribute to the advancement of the field through the use of sound sampling or experimental design, reliable analytical methodologies and robust statistical analyses. Although studies focusing on particular regions and target organisms are welcome, it is not the journal’s goal to publish essentially descriptive studies that provide results with narrow applicability, or are based on very small samples or pseudoreplication. Rather, Biochemical Genetics welcomes review articles that go beyond summarizing previous publications and create added value through the systematic analysis and critique of the current state of knowledge or by conducting meta-analyses. Methodological articles are also within the scope of Biological Genetics, particularly when new laboratory techniques or computational approaches are fully described and thoroughly compared with the existing benchmark methods. Biochemical Genetics welcomes articles on the following topics: Genomics; Proteomics; Population genetics; Phylogenetics; Metagenomics; Microbial genetics; Genetics and evolution of wild and cultivated plants; Animal genetics and evolution; Human genetics and evolution; Genetic disorders; Genetic markers of diseases; Gene technology and therapy; Experimental and analytical methods; Statistical and computational methods.