Miller Brendan, Haghani Amin, Ailshire Jennifer, Arpawong T Em
Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA.
Methods Mol Biol. 2020;2144:67-76. doi: 10.1007/978-1-0716-0592-9_6.
Testing hypotheses in human populations, then translating such findings into an experimental paradigm to test for causality can accelerate the rate of therapeutic discovery for many aging-related diseases. Integration of human genomics data has become much more accessible to molecular biologists in recent years due to the explosion of data availability and wealth of bioinformatic resources, tools, and methods that work together to minimize barriers related to its use. There are specific skill sets that can promote integration of human data into the work of molecular biologists, which include the ability to download, organize, store, and analyze human genomics data. In this chapter, key considerations and resources are presented, focusing on approaches that might be unfamiliar to molecular biologists, with regard to human subjects protection guidelines, heterogeneity in human genetics, data security and storage, programming languages, and training for data analysis.
在人群中检验假设，然后将这些发现转化为实验范式以检验因果关系，这可以加快许多与衰老相关疾病的治疗发现速度。近年来，由于数据可用性的爆炸式增长以及丰富的生物信息资源、工具和方法共同作用以尽量减少与使用相关的障碍，分子生物学家更容易获取人类基因组学数据。有一些特定的技能组合可以促进将人类数据整合到分子生物学家的工作中，包括下载、组织、存储和分析人类基因组学数据的能力。在本章中，将介绍关键考虑因素和资源，重点关注分子生物学家可能不熟悉的方法，涉及人类受试者保护指南、人类遗传学的异质性、数据安全与存储、编程语言以及数据分析培训。
