遗传力
SNP公司
单核苷酸多态性
遗传建筑学
生物
全基因组关联研究
遗传力缺失问题
遗传关联
统计
计算生物学
遗传学
数量性状位点
数学
基因型
基因
作者
Mingsheng Tang,Tong Wang,Zhang Xue-fen
摘要
Over the past decade, statistical methods have been developed to estimate single nucleotide polymorphism (SNP) heritability, which measures the proportion of phenotypic variance explained by all measured SNPs in the data. Estimates of SNP heritability measure the degree to which the available genetic variants influence phenotypes and improve our understanding of the genetic architecture of complex phenotypes. In this article, we review the recently developed and commonly used SNP heritability estimation methods for continuous and binary phenotypes from the perspective of model assumptions and parameter optimization. We primarily focus on their capacity to handle multiple phenotypes and longitudinal measurements, their ability for SNP heritability partition and their use of individual-level data versus summary statistics. State-of-the-art statistical methods that are scalable to the UK Biobank dataset are also elucidated in detail.
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