Efficient variance components analysis across millions of genomes
Efficient variance components analysis across millions of genomes
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DOI：
10.1038/s41467-020-17576-9
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发表时间：
2020-08-11
影响因子：
16.6
通讯作者：
Sankararaman, Sriram
中科院分区：
文献类型：
--
作者：
Pazokitoroudi, Ali;Wu, Yue;Sankararaman, Sriram
虽然方差分量分析已经成为复杂性状遗传学中的一个强大工具，但现有的拟合方差分量的方法不能很好地扩展到大规模的遗传变异数据集。在这里，我们提出了一种准确有效的方差分量分析方法：能够在几个小时内对一百万个基因分型为一百万个SNP的个体估计一百个方差分量。我们说明了我们的方法在估计和分区的基因型SNP（SNP遗传力）解释的性状变异的效用。分析来自30万个体的22个性状的基因型，跨越约800万个常见和低频率SNP，我们观察到每个等位基因的平方效应大小随着次要等位基因频率（MAF）和连锁不平衡（LD）的降低而增加，这与负选择的作用一致。将遗传性划分为28个功能注释，我们观察到哮喘、湿疹、甲状腺和自身免疫性疾病中FANTOM 5增强子的遗传性富集。方差分量分析可用于各种应用，包括遗传力估计和关联作图。在这里，作者提出了一种计算效率高的方法，可扩展到非常大的GWAS数据集，并使用它对英国生物银行的22个性状进行遗传分析
While variance components analysis has emerged as a powerful tool in complex trait genetics, existing methods for fitting variance components do not scale well to large-scale datasets of genetic variation. Here, we present a method for variance components analysis that is accurate and efficient: capable of estimating one hundred variance components on a million individuals genotyped at a million SNPs in a few hours. We illustrate the utility of our method in estimating and partitioning variation in a trait explained by genotyped SNPs (SNP-heritability). Analyzing 22 traits with genotypes from 300,000 individuals across about 8 million common and low frequency SNPs, we observe that per-allele squared effect size increases with decreasing minor allele frequency (MAF) and linkage disequilibrium (LD) consistent with the action of negative selection. Partitioning heritability across 28 functional annotations, we observe enrichment of heritability in FANTOM5 enhancers in asthma, eczema, thyroid and autoimmune disorders. Variance components analysis may be used for a variety of applications including heritability estimation and association mapping. Here, the authors present a computationally efficient method, scalable to extremely large GWAS datasets, and use it for heritabilty analysis of 22 traits from UK Biobank