Rapid advances in metabolomics technology create enormous challenges for the development of data processing and visualization techniques that enable biological scientists to gain insight from complex data sets. Although programming libraries are available for informaticians, there remains a need for powerful, user-friendly software to support biological specialists in analysing metabolomics data.
From raw data to the biological context of samples, the pipeline guides users through each core step in LC– MS data analysis. World-wide collaboration between groups is enabled by sharing both experimental designs and results online, overcoming limitations in big-data transfer. A robust and systematic statistical analysis is built into the pipeline, enabling users to differentiate and report both identified and annotated metabolites according to the Metabolomics Standard Initiative (MSI). State-of-the-art, multi-scale, multi-viewpoint visualization allows scientists to navigate and extract relevant information from sample data and to examine this information in a biological context.
PiMP is currently being developed by Glasgow Polyomics. The ultimate goal of our software is to standardize and automate metabolomics analysis by integrating all steps of a study -- from planning to analysis to biological impact reporting -- into one comprehensive tool. If you are a developer that wants to contribute to PiMP contact us here.