Biology from bioinformatics: data analytical and visualisations tools to gain new understandings from quantitative mass spectrometry

生命科学研究越来越多地使用高科技仪器进行，产生了大量数据。反过来，整个科学正在从以知识为基础的学科转变为大数据学科。其中一些技术被称为“组学”--来自基因组学(大规模研究基因)、蛋白质组学(蛋白质)和代谢组学(代谢物)。蛋白质是细胞中的功能分子，通过研究不同蛋白质在细胞中存在的水平(例如，比较健康细胞和患病细胞)，我们可以了解整个系统是如何运行的(或出现问题)，我们可以开始了解个别蛋白质所发挥的功能。蛋白质组学普遍使用的技术是质谱学(MS)，它能够从单个样本中测量数千种蛋白质。组学研究中最大的挑战之一是仪器产生的往往复杂和噪声的数据与对数据分析定制软件的需求之间的相互作用。学术研究小组和工业组织(商业仪器和软件制造商)正在积极开发这两个领域--确保学术研究和开发对工业产生最大影响确实是一个重大挑战。在蛋白质组学方面，有各种商业和免费/开放源码的软件包，能够分析从MS收集的原始数据，给出已识别的蛋白质列表，以及感兴趣的样品中或样品之间的丰度值。其中一个很受欢迎的套装名为Progensis QI，由仪器制造商Waters在国际上销售。Waters是一家大型全球性公司，总部位于英国曼彻斯特附近。然而，在蛋白质组学领域，目前缺乏一个好的软件来获取量化的蛋白质列表，并进行下游数据分析，以达到对生物系统的真正了解，这是利用蛋白质组学技术进行研究的科学家所要求的。这些下游分析包括可视化大型数据集以检查数据质量，并开始了解感兴趣系统中哪些蛋白质组可能发生变化。还有必要进行专门的统计分析，以确保只有重要的结果才能用于进一步研究和公布。在这个项目中，一位学术生物学家和数据分析师(Dean Hammond博士)将参与行业交流，直接与Waters合作，开发新的蛋白质组学数据分析软件，开发一个名为ProteoAnalytics的软件包。该程序包将能够从Progensis QI(和其他合适的上游程序包)获取信息，使生物学家能够轻松获得用于数据解释的尖端方法(例如绘制蛋白质与生物路径的图谱)，执行专门的统计分析，创建独特而强大的大型数据集可视化，并帮助用户为科学出版物准备高质量的数字和图表。该软件将使Waters能够非常迅速地了解为用户工作的功能，并将帮助蛋白质组科学家执行大规模数据分析。这次交流将使哈蒙德博士能够将他在学术蛋白质组学数据分析方面的知识带到Waters，并在软件开发方面获得行业视角的经验。这一交换还使首席研究员(领导一个学术软件开发小组的Andy Jones博士)与Waters的商业软件开发团队建立了协作伙伴关系。

Life sciences research is increasingly being performed using high-tech instrumentation, producing vast quantities of data. In turn, the science as a whole is being transformed from a knowledge-based discipline, into a Big Data discipline. Some of these techniques are called "omics" - from genomics (studying genes on a large scale), proteomics (proteins) and metabolomics (metabolites). Proteins are the functional molecules in cells, and by studying the levels at which different proteins are present in cells (for example comparing healthy versus diseased cells), we can understand how the system as a whole is behaving (or going wrong) and we can begin to understand the function played by the individual proteins. The pervasive technique used for proteomics is mass spectrometry (MS), which is capable of measuring many thousands of proteins from a single sample. One of the biggest challenges in omics research is the interplay between often complex and noisy data produced by the instrument and the requirement for bespoke software for data analysis. Both areas are under active development in academic research groups and by industrial organisations (commercial instrument and software manufacturers) - and it is indeed a major challenge ensuring that academic research and development has maximum impact on industry. In proteomics, there are various software packages, both commercial and free/open source, capable of analysing the raw data collected from MS to give a list of proteins identified, along with an abundance value in or between samples of interest. One popular package is called Progenesis QI - marketed internationally by instrument manufacturer Waters. Waters are a large global corporation, with headquarters near Manchester, UK. However, in proteomics, there is currently a shortage of good software for taking the quantified protein list, and performing downstream data analysis to arrive at a real understanding of the biological system, as required by scientists that make use of proteomics techniques in their research. These downstream analyses include visualising the large data set to check the data quality, and starting to understand which groups of proteins may be changing in the system of interest. It is also necessary to perform specialised statistical analyses to ensure that only significant results are taken for further study and published. In this project, an academic biologist and data analyst (Dr Dean Hammond) will take part in an industry interchange, to work directly with Waters, to develop new software for proteomics data analysis, developing a package called ProteoAnalytics. The package will be able to take input from Progenesis QI (and other suitable upstream packages), enabling biologists easy access to cutting-edge methods for data interpretation (such as mapping proteins to biological pathways), performing specialised statistical analyses, creating unique and powerful visualisations of large data sets, and assisting users to prepare high-quality figures and charts for scientific publications. The software will enable Waters to understand very rapidly the features that work for users, and will assist proteome scientists to perform large scale data analyses. The interchange will allow Dr Hammond to take his knowledge of academic proteomics data analysis to Waters, and gain experience of the industry perspective in software development. The interchange also enables the creation of a collaborative partnership between the principal investigator (Dr Andy Jones, who leads an academic software development group) with the commercial software development team at Waters.