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Workflow4Metabolomics: A collaborative research infrastructure for computational metabolomics
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Paper reference: Giacomoni et al. (2014) Workflow4Metabolomics: A collaborative research infrastructure for com- putational metabolomics. Bioinformatics http://dx.doi.org/10.1093/bioinformatics/btu813
Paper reference: Giacomoni et al. (2014) Workflow4Metabolomics: A collaborative research infrastructure for computational metabolomics. Bioinformatics http://dx.doi.org/10.1093/bioinformatics/btu813.
In the context of an emergent and fast evolving science, the development of various tools dedicated to metabolomic data processing and data analysis increased. Because metabolomic analyses require a variety of steps involving various disciplines from analytical chemistry to statistics and bioinformatics, it requires many skills and expertise. However, despite this abundance of tools, standardization is lacking in these diversity of programs, as well as infrastructure to handle and link the different steps of metabolomic analyses. We recently implemented Workflow4Metabolomics (W4M), a collaborative online platform hosting and providing a full pipelinefor metabolomics from data preprocessing to annotation including statistical analysis. It is not designed to respond to only one specific type of metabolomic analysis, but to cover a maximum range of possible approaches - as metabolomics is a complex science that can be studied through various complementary analytical techniques. Thus, more than just gathering programs, W4M provides relevant combinations of generic and specific tools, a large part of which being developed and sustained by the partners providing this virtual research environment (VRE). Moreover, using Galaxy, a web-based platform technology, W4M provides modules from various sources and of various types. This platform allows hosted tools to be run and linked together via an instinctive and ergonomic interface, which is beneficial for both beginners and experts in metabolomics. W4M gets its strength from the collaboration of complementary teams from bioinformatics and metabolomics environment. Initiated by the collaboration between two platforms, it gathers today six research teams and platforms with a higher diversity in skills and expertise. It allows a continuous enrichment in the service provided, with addition of new modules and new possible workflows dedicated to cover a large scope of the increasing needs of the metabolomic community. Moreover,the ‘open-source’ aspect of this platform allows to open it to new collaborators bringing specific expertise that can be highlighted and disseminated in the metabolomic community
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