Prospects of Fine-Mapping Trait-Associated Genomic Regions by Using Summary Statistics from Genome-wide Association Studies
Prospects of Fine-Mapping Trait-Associated Genomic Regions by Using Summary Statistics from Genome-wide Association Studies
复制标题
DOI：
10.1016/j.ajhg.2017.08.012
复制
发表时间：
2017-10-05
影响因子：
9.8
通讯作者：
Pirinen, Matti
中科院分区：
文献类型：
--
作者：
Benner, Christian;Havulinna, Aki S.;Pirinen, Matti
在过去的几年中，各种新的统计方法已经开发出精细定位与使用的汇总统计全基因组关联研究（GWAS）。虽然这些方法需要关于变异体之间的连锁不平衡（LD）的信息，但还没有全面评估参考基因型面板中LD结构的估计与原始个体水平GWAS数据的估计相比如何执行。使用来自芬兰和英国生物银行的人群基因型数据，我们在这里表明，来自目标人群的1000个个体的参考面板对于多达10,000个个体的GWAS队列是足够的，而较小的面板，如来自1000个基因组计划的面板，应该避免。我们还表明，无论是理论上还是经验上，参考面板的大小需要与GWAS样本量成比例;这对这些方法在正在进行的GWAS荟萃分析和大型生物库研究中的应用具有重要影响。最后，我们提供了软件工具，并建议分享LD信息的做法，更有效地利用遗传学研究中的汇总统计。
During the past few years, various novel statistical methods have been developed for fine-mapping with the use of summary statistics from genome-wide association studies (GWASs). Although these approaches require information about the linkage disequilibrium (LD) between variants, there has not been a comprehensive evaluation of how estimation of the LD structure from reference genotype panels performs in comparison with that from the original individual-level GWAS data. Using population genotype data from Finland and the UK Biobank, we show here that a reference panel of 1,000 individuals from the target population is adequate for a GWAS cohort of up to 10,000 individuals, whereas smaller panels, such as those from the 1000 Genomes Project, should be avoided. We also show, both theoretically and empirically, that the size of the reference panel needs to scale with the GWAS sample size; this has important consequences for the application of these methods in ongoing GWAS meta-analyses and large biobank studies. We conclude by providing software tools and by recommending practices for sharing LD information to more efficiently exploit summary statistics in genetics research.