Informatics tools for analysis of quantitative proteomics data

The science of proteomics aims to characterise the proteins present in cells and tissues on a potentially genome-wide scale, offering opportunities to advance biomedical science by identifying changes in the proteome linked to biological function and disease. However, until recently, it has been a largely qualitative science - a protein is either there or not. Techniques are now being developed in labs including those supporting this bid which allow differences in protein levels to be quantified using mass spectrometry as the analytical technique. Unfortunately, the appropriate software tools for processing this information in a simple manner are not readily available to academic groups, and those tools that are suffer from problems (they are specific to one technique, difficult to use, and don't write out the results in standard formats for submission to databases). We plan to address this by developing a single software solution which unifies many of the formats and enable or speed up data capture and analysis in this area

Quantitative proteomics has arrived on a near genome-wide scale thanks to advances in stable isotope-based labelling techniques and mass spectrometry. The attendant software for capturing, processing, analysing and disseminating the data have not keep up with developments however, and open source tools are either unavailable, not universal, or incredibly difficult for most mass spectrometry groups to install and deploy. We are in a favourable position, having experience dealing with mass spectrometry data and have close connections with labs using technologies such as SILAC and ITRAQTM, as well as groups innovating novel absolute quantification techniques such as Beynon (Liverpool) and Gaskell (Manchester). This grant will extend and develop XML schema to capture these novel data types, extend an existing 'wizard' to capture the data from vendor-specific and PSI-supported formats, develop further the mean to analyse the data and finally, support the export of the proteomic data sets in PSI standard XML format, such as PRIDE-XML