Neurospsychiatric Genetics Group, Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany.
Hum Mutat. 2012 Sep;33(9):1366-72. doi: 10.1002/humu.22149. Epub 2012 Jul 12.
Tens of thousands of genetic association studies investigating the influence of common polymorphisms on disease susceptibility have been published to date. These include ∼1,000 genome-wide association studies (GWAS). This vast amount of data in the field of complex genetics is becoming increasingly difficult to follow and interpret. It can be expected that the situation will become even more complex with the advent of association projects using "next-generation" technologies. One of the aims of the Human Variome Project is to concatenate such data in meaningful ways, for example, within the context of publicly available field synopses. Here, we present various examples of online genetic association databases developed by our group for neuropsychiatric disorders. One integral part of this model is the systematic inclusion of data from large-scale genotyping projects, for example, GWAS, while respecting the privacy of data contributors. We believe that our database approach may serve as a viable model that can be readily applied to other fields and ultimately improve our understanding of the genetic forces driving common human conditions.
迄今已有数以万计的针对常见多态性对疾病易感性影响的遗传关联研究发表,其中包括约 1000 项全基因组关联研究(GWAS)。在复杂遗传学领域,这些海量的数据正变得越来越难以跟踪和解释。可以预计,随着使用“下一代”技术的关联项目的出现,情况将变得更加复杂。人类变异组计划的目标之一是以有意义的方式串联这些数据,例如在公开的领域概要的上下文中。在这里,我们展示了我们小组为神经精神障碍开发的各种在线遗传关联数据库的示例。该模型的一个组成部分是系统地纳入来自大规模基因分型项目的数据,例如 GWAS,同时尊重数据贡献者的隐私。我们相信,我们的数据库方法可以作为一种可行的模式,很容易应用于其他领域,并最终帮助我们更好地理解导致常见人类疾病的遗传因素。