Crawford Dana C, Dilks Holli Hutcheson
Center for Human Genetics Research, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee, USA.
Curr Protoc Hum Genet. 2011 Jan;Chapter 1:Unit1.3. doi: 10.1002/0471142905.hg0103s68.
The identification of genomic loci linked to or associated with human disease has been greatly facilitated by the evolution of genotyping strategies and techniques. The success of these strategies continues to be based upon clear clinical assessment, accurate sample handling, and careful data management, but also increasingly upon experimental design. Technological advances in the field of genotyping have permitted increasingly complex and large population studies to be performed. An understanding of publicly available genetic variation databases, including an awareness of the limitations of these data, and an appreciation of the strategic approaches that should be used to exploit this information will provide tremendous insight for researchers are aiming to utilize this accessible technology. As genome-wide association studies (GWAS) and Next Generation (NextGen) sequencing become the mainstays of genetic analyses, it is important that their technical strengths and limitations, as well as their impact on study design, be understood before use in a linkage or genetic association study.
基因分型策略和技术的发展极大地推动了与人类疾病相关或关联的基因组位点的识别。这些策略的成功仍然基于清晰的临床评估、准确的样本处理和细致的数据管理，但也越来越依赖于实验设计。基因分型领域的技术进步使得越来越复杂和大规模的人群研究得以开展。了解公开可用的遗传变异数据库，包括认识到这些数据的局限性，并理解应采用的利用这些信息的策略方法，将为旨在利用这项便捷技术的研究人员提供巨大的洞察力。随着全基因组关联研究（GWAS）和新一代（NextGen）测序成为遗传分析的主流，在将其用于连锁或基因关联研究之前，了解它们的技术优势和局限性以及它们对研究设计的影响非常重要。
