Emmert-Streib Frank, Dehmer Matthias, Yli-Harja Olli
Predictive Society and Data Analytics Lab, Faculty of Information Technology and Communication Sciences, Tampere University, Tampere, Finland.
Institute of Biosciences and Medical Technology, Tampere, Finland.
Front Cell Dev Biol. 2019 Dec 17;7:349. doi: 10.3389/fcell.2019.00349. eCollection 2019.
Modern molecular high-throughput devices, e.g., next-generation sequencing, have transformed medical research. Resulting data sets are usually high-dimensional on a genomic-scale providing multi-factorial information from intertwined molecular and cellular activities of genes and their products. This genomics-revolution installed precision medicine offering breathtaking opportunities for patient's diagnosis and treatment. However, due to the speed of these developments the quality standards of the involved data analyses are lacking behind, as exemplified by the infamous Duke Saga. In this paper, we argue in favor of a two-stage cooperative serve model that couples data generation and data analysis in the most beneficial way from the perspective of a patient to ensure data analysis quality standards including reproducible research.
现代分子高通量设备，例如下一代测序技术，已经改变了医学研究。所产生的数据集通常在基因组规模上是高维的，提供了来自基因及其产物相互交织的分子和细胞活动的多因素信息。这场基因组学革命催生了精准医学，为患者的诊断和治疗带来了惊人的机遇。然而，由于这些发展的速度，相关数据分析的质量标准却滞后了，臭名昭著的杜克事件就是例证。在本文中，我们主张采用一种两阶段合作服务模式，从患者的角度以最有益的方式将数据生成与数据分析结合起来，以确保包括可重复研究在内的数据分析质量标准。
