Li Ruowang, Kim Dokyoon, Ritchie Marylyn D
Bioinformatics & Genomics Graduate Program, The Pennsylvania State University, University Park, PA 16802, USA.
Biomedical & Translational Informatics Institute, Geisinger Health System, Danville, PA 17821, USA.
Pharmacogenomics. 2017 Jun;18(8):807-820. doi: 10.2217/pgs-2016-0152. Epub 2017 Jun 14.
The scale and scope of pharmacogenomics research continues to expand as the cost and efficiency of molecular data generation techniques advance. These new technologies give rise to enormous opportunity for the identification of important genetic and genomic factors important for drug treatment response. With this opportunity come significant challenges. Most of these can be categorized as 'big data' issues, facing not only pharmacogenomics, but other fields in the life sciences as well. In this review, we describe some of the analysis techniques and tools being implemented for genetic/genomic discovery in pharmacogenomics.
随着分子数据生成技术的成本降低和效率提高,药物基因组学研究的规模和范围不断扩大。这些新技术为识别对药物治疗反应至关重要的重要遗传和基因组因素带来了巨大机遇。伴随着这个机遇也带来了重大挑战。其中大多数可归类为“大数据”问题,不仅药物基因组学面临这些问题,生命科学的其他领域也面临这些问题。在本综述中,我们描述了一些正在药物基因组学中用于遗传/基因组发现的分析技术和工具。