Center for Proteomics and Metabolomics, Leiden University Medical Center, Albinusdreef 2, 2333ZA, Leiden, The Netherlands.
Analyst. 2020 Jun 7;145(11):3801-3808. doi: 10.1039/d0an00272k. Epub 2020 May 6.
Providing maximum information on the provenance of scientific results in life sciences is getting considerable attention since the widely publicized reproducibility crisis. Improving the reproducibility of data processing and analysis workflows is part of this movement and may help achieve clinical deployment quicker. Scientific workflow managers can be valuable tools towards achieving this goal. Although these platforms are already well established in the field of genomics and other omics fields, in metabolomics scripts and dedicated software packages are still more popular. However, versatile workflows for metabolomics exist in the KNIME and Galaxy platforms. We will here summarize the available options of scientific workflow managers dedicated to metabolomics analysis.
自从生命科学领域广泛报道的可重复性危机以来,提供科学成果出处的最大信息量越来越受到关注。提高数据处理和分析工作流程的可重复性是这一运动的一部分,并且可能有助于更快地实现临床应用。科学工作流管理器是实现这一目标的有价值工具。尽管这些平台在基因组学和其他组学领域已经得到很好的应用,但在代谢组学中,脚本和专用软件包仍然更受欢迎。然而,在 KNIME 和 Galaxy 平台上存在用于代谢组学的通用工作流程。我们将在这里总结专门用于代谢组学分析的科学工作流管理器的可用选项。