Systems vaccinology and big data in the vaccine development chain

Raeven, René H. M.; van Riet, Elly; Meiring, Hugo D.; Metz, Bernard; Kersten, Gideon F. A.

One of the difficulties in systems approaches is the amount of data. Statistical evaluation, visualization and extracting meaningful conclusions are major challenges and require multiple tools and expertises. 74, 75 New technologies in systems vaccinology such as metabolomics may require different statistical and bioinformatic analysis strategies compared with transcriptomics and proteomics data sets, as described by Ren et al. 76 Visualization of data from full genomes or proteomes was initially performed with tools applying e.g. heatmaps, Venn diagrams and network analysis, e.g. with Cytoscape. 77 These allowed visualization of numerous individual data points or groups, but also the clustering of related data points. Additionally, the generation of multiple systems-scale data sets enables the comparison of immune responses induced by different vaccines in an unbiased manner. 78, 79 Hierarchical Stochastic Neighborhood Embedding (HSNE) enables us to visualize data of cellular composition of millions of cells in detail up to the single-cell level. 80 Although these graphs provide an easier perspective on trends in the data sets, they are not designed to provide information on the biological function of individual data points. The development of data mining tools ( Fig. 1 ) has given scientists a handle to translate their data sets into the description of relevant biological processes. 81 This allows for investigation of the involvement and mutual interaction of pathways, processes and cell types. Tools that are focused on pathway analysis include DAVID, 82 Pathway-Express, 83 Gene Onthology (GO) 84 and the Kyoto Encyclopedia of Genes and Genomes (KEGG). 85 With BioGPS, the involvement of cells or the different stages in cell activation can be investigated. 86 This has also led to the development of specialized databases for specific research topics. For example, InnateDB contains data on innate immune responses 87 while INTERFEROME focuses on interferon-related processes 88 and the CEMiTool can be used for co-expression analyses and discovery of functionality of genes. 89 For the discovery and analysis of the repertoire of T-and B-cell receptor sequences, VDJviz can be applied for the routine analysis and quality control of sequencing of immune repertoires 90 and VDJdb is designed for the annotation of T-cell receptor repertoire data. 91 These databases evolve and expand continuously based on novel data, scientific insights and technologies. Depending on the choice of data mining tools, the outcome of results might differ. However, within the Human Vaccines Project, 92 researchers demonstrated that there was no difference in the outcome of their data when it was either analyzed using a tool based on prior knowledge, in this case the NetAnalyst platform, or with an unbiased tool, DIABLO.