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

用于生物质谱存储库中的原始数据和分析数据的远程流式 3D 可视化平台

• 批准号: BB/K016733/1
• 负责人: Andrew Dowsey
• 金额: $ 15.33万
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2013
• 资助国家: 英国
• 起止时间: 2013 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FK016733%2F1
• 关键词: Remote; streaming; 3D; visualisation; platform

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.

生物学家越来越希望了解控制每个生物体功能的基因、代谢物和蛋白质的构建模块之间的复杂相互作用。系统生物学领域的出现是为了克服传统还原论方法的缺陷，这种方法已经确定了构建模块本身和许多个体相互作用，但无法推断出这些模块的系统如何一致地行动和反应。系统生物学的应用是广泛的，因为它有望彻底改变我们对植物，动物和人类健康过程的理解，以及它们如何在疾病下分解以及如何避免这种分解。通常，系统生物学方法从特定生物样品的“快照”开始。质谱法是一种普遍的技术，用于获得样品中蛋白质或代谢物的快照，它通过电离样品，然后根据产生的电荷测量每个组成化合物的质量和数量来实现。这通常不足以完全分离出样品，因此使用液相或气相色谱的前一阶段来提供初始分离。由于技术和生物学的差异，有必要对样品进行多次分析，以获得可靠的读数。有趣的生化物质也可以被分解成特征片段，并对这些片段进行测量，这通常可以对该生化物质进行可靠的鉴定。所有这些都导致系统生物学逐渐成为一门计算学科。然而，由于数据集变得如此之大，因此存在这样的危险，即该过程变得越来越不透明，质谱从业者无法访问，因此更有可能被用作“黑匣子”。因此，至关重要的是，要有工具和平台，使专家用户能够通过检查所获得的原始数据来核实、验证和解释结果，否则处理中的偏见、错误和错误假设将经常被忽视。然而，大规模的数据集是一个挑战，因为现有的工具加载和处理数据进行可视化的速度很慢，这严重限制了生产力，并由于内存有限而无法对整个实验进行综合比较。造成这种情况的部分原因是，现有的数据格式不是为了简化感兴趣区域的检索或快速、高效可视化所需的不同细节级别而设计的。我们建议为符合标准的数据设计这样的表示形式，并由此我们将立即首次展示来自本地存储的交互式3D可视化。由于内存开销问题也得到了缓解，因此可以实现完整实验结果和原始数据的新型可视化方案，极大地促进了MS分析的质量控制、验证、确认和专家解释。此外，通过开发专门的图像压缩技术，我们将演示通过互联网进行实时远程可视化，以类似于谷歌地球的方式，但首次扩展了质谱可视化的需求。位于剑桥欣克斯顿的欧洲生物信息学研究所最近通过ProteomeXchange联盟将原始数据存入他们的PRIDE公共数据库，该库存储了来自世界各地的大量公共资助实验。截至2012年9月，它拥有3.24亿个质谱。我们的远程可视化平台将展示通过在线出版物和网络资源连接的即时和无缝原始数据访问的潜力，这将大大改善这些战略社区数据源的设施，可访问性和重用性。