Computational Workflows and Workflow Engines
Computational analysis of high-dimension and high-volume metabolomics data is a complex, time-consuming process including many steps, some of which still being the focus of intense research. Workflow management environments applied in metabolomics and cross-omics analyses are therefore an essential requirement to allow standardisation of bioinformatics analysis, provide access to the metabolomics community, and produce high- quality, reproducible results in a time-effective manner: on the one hand, experimenters should be able to easily select the tools via a graphical interface, choose the parameters, run the workflow and save/share the results; on the other hand, developers should be able to integrate new tools seamlessly into the environment. A few open-source workflows have recently been applied in different environments including Galaxy-M, Workflow4Metabolomics, MetaDB and MetaboAnalyst. There is a growing need for the international metabolomics community to understand the availability and capability of these workflow environments, and provide input into on-going development and interoperability.
Target Audience: metabolomics data producers, researchers
- Understanding different workflow environments
- Current shortcomings and improvements that could help widen the adoption of these type of tools within the metabolomics community
- Feedback from users