title: Pathomx: an interactive workflow-based tool for the analysis of metabolomic data.
abstract: BACKGROUND
  Metabolomics is a systems approach to the analysis of cellular processes through small-molecule metabolite profiling. Standardisation of sample handling and acquisition approaches has contributed to reproducibility. However, the development of robust methods for the analysis of metabolomic data is a work-in-progress. The tools that do exist are often not well integrated, requiring manual data handling and custom scripting on a case-by-case basis. Furthermore, existing tools often require experience with programming environments such as MATLAB® or R to use, limiting accessibility. Here we present Pathomx, a workflow-based tool for the processing, analysis and visualisation of metabolomic and associated data in an intuitive and extensible environment.
  
  
  RESULTS
  The core application provides a workflow editor, IPython kernel and a HumanCyc™-derived database of metabolites, proteins and genes. Toolkits provide reusable tools that may be linked together to create complex workflows. Pathomx is released with a base set of plugins for the import, processing and visualisation of data. The IPython backend provides integration with existing platforms including MATLAB® and R, allowing data to be seamlessly transferred. Pathomx is supplied with a series of demonstration workflows and datasets. To demonstrate the use of the software we here present an analysis of 1D and 2D (1)H NMR metabolomic data from a model system of mammalian cell growth under hypoxic conditions.
  
  
  CONCLUSIONS
  Pathomx is a useful addition to the analysis toolbox. The intuitive interface lowers the barrier to entry for non-experts, while scriptable tools and integration with existing tools supports complex analysis. We welcome contributions from the community.
authors.affiliation: Rheumatology Research Group, Centre for Translational Inflammation Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2WD, UK. mxf793@bham.ac.uk.
authors.forename: Martin A
authors.initials: MA
authors.lastname: Fitzpatrick
authors.affiliation: Rheumatology Research Group, Centre for Translational Inflammation Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2WD, UK. c.m.mcgrath@bham.ac.uk.
authors.forename: Catherine M
authors.initials: CM
authors.lastname: McGrath
authors.affiliation: Rheumatology Research Group, Centre for Translational Inflammation Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2WD, UK. s.p.young@bham.ac.uk.
authors.forename: Stephen P
authors.initials: SP
authors.lastname: Young
mesh_terms: D002478:Cells, Cultured; D019295:Computational Biology / Q000379:methods*; D016208:Databases, Factual; D006801:Humans; D008264:Macrophages / Q000166:cytology / Q000378:metabolism*; D009682:Magnetic Resonance Spectroscopy; D053858:Metabolic Networks and Pathways; D055432:Metabolomics / Q000379:methods*; D015203:Reproducibility of Results; D012984:Software; D057188:Workflow