Spicer Rachel, Salek Reza M, Moreno Pablo, Cañueto Daniel, Steinbeck Christoph
European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD UK.
Metabolomics Platform, IISPV, DEEEA, Universitat Rovira i Virgili, Campus Sescelades, Carretera de Valls, s/n, 43007 Tarragona, Catalonia Spain.
Metabolomics. 2017;13(9):106. doi: 10.1007/s11306-017-1242-7. Epub 2017 Aug 9.
The field of metabolomics has expanded greatly over the past two decades, both as an experimental science with applications in many areas, as well as in regards to data standards and bioinformatics software tools. The diversity of experimental designs and instrumental technologies used for metabolomics has led to the need for distinct data analysis methods and the development of many software tools.
To compile a comprehensive list of the most widely used freely available software and tools that are used primarily in metabolomics.
The most widely used tools were selected for inclusion in the review by either ≥ 50 citations on Web of Science (as of 08/09/16) or the use of the tool being reported in the recent Metabolomics Society survey. Tools were then categorised by the type of instrumental data (i.e. LC-MS, GC-MS or NMR) and the functionality (i.e. pre- and post-processing, statistical analysis, workflow and other functions) they are designed for.
A comprehensive list of the most used tools was compiled. Each tool is discussed within the context of its application domain and in relation to comparable tools of the same domain. An extended list including additional tools is available at https://github.com/RASpicer/MetabolomicsTools which is classified and searchable via a simple controlled vocabulary.
This review presents the most widely used tools for metabolomics analysis, categorised based on their main functionality. As future work, we suggest a direct comparison of tools' abilities to perform specific data analysis tasks e.g. peak picking.
在过去二十年中,代谢组学领域得到了极大的扩展,它既是一门应用于许多领域的实验科学,在数据标准和生物信息学软件工具方面也是如此。用于代谢组学的实验设计和仪器技术的多样性导致了对不同数据分析方法的需求以及许多软件工具的开发。
编制一份主要用于代谢组学的最广泛使用的免费软件和工具的综合列表。
通过在科学网(截至2016年9月8日)上被引用≥50次或在最近的代谢组学协会调查中被报告使用的工具,选择最广泛使用的工具纳入综述。然后根据仪器数据类型(即液相色谱 - 质谱联用、气相色谱 - 质谱联用或核磁共振)及其设计的功能(即预处理和后处理、统计分析、工作流程和其他功能)对工具进行分类。
编制了一份最常用工具的综合列表。在其应用领域的背景下以及与同一领域的可比工具相关的情况下,对每个工具进行了讨论。一个包含更多工具的扩展列表可在https://github.com/RASpicer/MetabolomicsTools上获取,该列表通过简单的受控词汇进行分类和搜索。
本综述介绍了代谢组学分析中最广泛使用的工具,并根据其主要功能进行了分类。作为未来的工作,我们建议直接比较工具执行特定数据分析任务(例如峰检测)的能力。