Translational Genomics Research Institute (TGen), Phoenix, Arizona 85004, USA.
Nat Rev Genet. 2011 Sep 16;12(10):730-6. doi: 10.1038/nrg3067.
Access to genetic data across studies is an important aspect of identifying new genetic associations through genome-wide association studies (GWASs). Meta-analysis across multiple GWASs with combined cohort sizes of tens of thousands of individuals often uncovers many more genome-wide associated loci than the original individual studies; this emphasizes the importance of tools and mechanisms for data sharing. However, even sharing summary-level data, such as allele frequencies, inherently carries some degree of privacy risk to study participants. Here we discuss mechanisms and resources for sharing data from GWASs, particularly focusing on approaches for assessing and quantifying the privacy risks to participants that result from the sharing of summary-level data.
跨研究获取遗传数据是通过全基因组关联研究（GWAS）识别新遗传关联的一个重要方面。通过合并数万名个体的多个 GWAS 进行荟萃分析，通常会发现比原始个体研究更多的全基因组关联位点；这强调了用于数据共享的工具和机制的重要性。然而，即使共享汇总数据（如等位基因频率），也会对研究参与者带来一定程度的隐私风险。在这里，我们讨论了从 GWAS 中共享数据的机制和资源，特别是重点介绍了用于评估和量化因共享汇总数据而对参与者造成的隐私风险的方法。
