Pathomx: an interactive workflow-based tool for the analysis of metabolomic data

BMC Bioinformatics

Martin A Fitzpatrick¹  Catherine M McGrath¹  Stephen P Young¹ 

[1] Rheumatology Research Group, Centre for Translational Inflammation Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham B15 2WD, UK

关键词: Python;    Automation;    Workflow;    Visualisation;    Analysis;    nmr;    Omics;    Metabolomics;   

Others  :  1084484
DOI  :  10.1186/s12859-014-0396-9

 received in 2014-03-21, accepted in 2014-11-24,  发布年份 2014

【 摘 要 】

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 ¹H 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.

【 授权许可】

   
2014 Fitzpatrick et al.; licensee BioMed Central Ltd.

【 图 表 】

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