Institut Pasteur de Tunis, LR11IPT02, Laboratory of Transmission, Control and Immunobiology of Infections (LTCII), 1002 Tunis-Belvédère, Tunisia.
IBM Research Africa, 2001, Johannesburg, South Africa.
Genome Res. 2018 May;28(5):759-765. doi: 10.1101/gr.228460.117. Epub 2018 Apr 12.
Scientific research plays a key role in the advancement of human knowledge and pursuit of solutions to important societal challenges. Typically, research occurs within specific institutions where data are generated and subsequently analyzed. Although collaborative science bringing together multiple institutions is now common, in such collaborations the analytical processing of the data is often performed by individual researchers within the team, with only limited internal oversight and critical analysis of the workflow prior to publication. Here, we show how hackathons can be a means of enhancing collaborative science by enabling peer review before results of analyses are published by cross-validating the design of studies or underlying data sets and by driving reproducibility of scientific analyses. Traditionally, in data analysis processes, data generators and bioinformaticians are divided and do not collaborate on analyzing the data. Hackathons are a good strategy to build bridges over the traditional divide and are potentially a great agile extension to the more structured collaborations between multiple investigators and institutions.
科学研究在人类知识的进步和解决重要社会挑战的方法探索中起着关键作用。通常，研究是在特定的机构内进行的，数据就是在这些机构中产生并随后进行分析的。虽然现在常见的是多机构合作的科学研究，但在这种合作中，数据分析的处理通常是由团队中的个别研究人员完成的，在发表之前，只有有限的内部监督和对工作流程的关键分析。在这里，我们展示了黑客马拉松如何通过在分析结果发表之前进行同行评审，通过交叉验证研究设计或基础数据集来提高合作科学的水平，并推动科学分析的可重复性，从而成为增强合作科学的一种手段。传统上，在数据分析过程中，数据生成者和生物信息学家是分开的，不会合作分析数据。黑客马拉松是跨越传统鸿沟的好策略，并且可能是对多研究人员和机构之间更结构化合作的一种很好的敏捷扩展。
