Jonnagaddala Jitendra, Croucher Joanne L, Jue Toni Rose, Meagher Nicola S, Caruso Lena, Ward Robyn, Hawkins Nicholas J
Prince of Wales Clinical School, UNSW Australia.
Office of DVC-Research, University of Queensland.
Stud Health Technol Inform. 2016;225:387-91.
Cancer is the number one cause of death in Australia with colorectal cancer being the second most common cancer type. The translation of cancer research into clinical practice is hindered by the lack of integration of heterogeneous and autonomous data from various data sources. Integration of heterogeneous data can offer researchers a comprehensive source for biospecimen identification, hypothesis formulation, hypothesis validation, cohort discovery and biomarker discovery. Alongside the increasing prominence of big data, various translational research tools such as tranSMART have emerged that can converge and analyse different types of data. In this study, we show the integration of different data types from a significant Australian colorectal cancer cohort. Additionally, colorectal cancer datasets from The Cancer Genome Atlas were also integrated for comparison. These integrated data are accessible via http://www.tcrn.unsw.edu.au/transmart. The use of translational research tools for data integration can provide a cost-effective and rapid approach to translational cancer research.
癌症是澳大利亚的首要死因，结直肠癌是第二常见的癌症类型。来自各种数据源的异构和自主数据缺乏整合，阻碍了癌症研究向临床实践的转化。异构数据的整合可为研究人员提供一个全面的生物样本识别、假设形成、假设验证、队列发现和生物标志物发现的来源。随着大数据日益突出，各种转化研究工具（如tranSMART）应运而生，它们可以汇聚和分析不同类型的数据。在本研究中，我们展示了来自澳大利亚一个重要结直肠癌队列的不同数据类型的整合。此外，还整合了来自癌症基因组图谱的结直肠癌数据集进行比较。这些整合后的数据可通过http://www.tcrn.unsw.edu.au/transmart获取。使用转化研究工具进行数据整合可为转化癌症研究提供一种经济高效且快速的方法。
