Remote streaming 3D visualisation platform for raw and analysed data from biological mass spectrometry repositories

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Biologists are increasing wishing to understand the complex interactions between the building blocks of genes, metabolites and proteins that control the function of every living organism. The field of systems biology has emerged to overcome the deficiencies of the traditional reductionist approach, which has identified the building blocks themselves and many of the individual interactions but has not been able to deduce how systems of these blocks act and react in unison. The application of systems biology is widespread, as it promises to revolutionise our understanding of healthy processes in plants, animals and humans, as well as how they break down under disease and how this breakdown can be averted. Often the systems biology approach starts with a 'snapshot' of a particular biological sample. Mass spectrometry is a pervasive technique for gaining a snapshot of the proteins or metabolites in a sample, and it does this by ionising the sample and then measuring each constituent compound's mass and quantity based on the resulting charge. This is often not enough to separate out the sample fully and therefore a preceding phase of liquid or gas chromatography is used to provide an initial separation. Due to technical and biological variations, it will be necessary to analyse the sample a number of times to get reliable readings. Interesting biochemicals can also be broken up into characteristic fragments and these measured, which often gives a confident identification of that biochemical. All this has led systems biology to become a progressively computational discipline. Since the datasets are becoming so large, however, that there is a danger that the process becomes more and more opaque and inaccessible to mass spectrometry practitioners and so more likely to be used as a 'black box'. It is therefore vitally important that tools and platforms are available that allow expert user verification, validation and interpretation of results by checking the raw data acquired, otherwise bias, errors and false assumptions in processing will be routinely overlooked. The massive datasets prove a challenge, however, as existing tools are slow to load and process the data for visualisation which severely limits productivity and precludes the integrated comparison of whole experiments due to limited memory. Part of the reason for this is that existing data formats have not been designed for streamlined retrieval of regions of interest or at varying levels of detail necessary for fast, efficient visualisation. We propose to design such a representation for standards-complaint data, and from that we will demonstrate interactive 3D visualisations from local storage for the first time without delay. Since memory overhead issues are also mitigated, novel visualisation schemes integrating results and raw data across complete experiments will be possible, greatly facilitating the quality control, verification, validation and expert interpretation of MS analyses.Furthermore, through development of specialised image compression, we will demonstrate real-time remote visualisation across the Internet, in a manner similar to Google Earth but for the first time extended for the demands of mass spectrometry visualisation. The European Bioinformatics Institute at Hinxton, Cambridge, has through the ProteomeXchange consortium recently launched raw data deposition into their PRIDE public data repositories, which stores vast amount of publically-funded experiments from around the world. As of September 2012, it holds 324 million mass spectra. Our remote visualisation platform will demonstrate the potential for immediate and seamless raw data access linked by online publications and web resources, which would lead to substantially improved facility, accessibility and re-use of these strategic community data sources.