Department of Computer Science, University of California, Los Angeles, Los Angeles, CA 90095, USA.
Am J Hum Genet. 2013 Apr 4;92(4):558-64. doi: 10.1016/j.ajhg.2013.03.010.
Quantifying heritability, the amount of genetic contribution in a complex trait, has been of fundamental interest to geneticists for decades. Recently, partitioning the heritability accounted for by common variants into the contributions of genomic regions has received a lot of attention given its important applications for understanding the genetic architecture of complex traits. Current methods partition the total heritability by jointly estimating the contributions of all regions. However, these methods are computationally intractable and can be inaccurate when the number of regions is large. In this paper, we present an alternative approach that partitions the total heritability into the contributions of an arbitrary number of regions. We demonstrate by using simulations that our approach is more accurate and computationally efficient than current approaches. Using a data set from a genome-wide association study on human height, we demonstrate the utility of our method by estimating the heritability contributions of chromosomes and subchromosomal regions.
几十年来,量化遗传率(复杂性状中遗传贡献的程度)一直是遗传学家非常感兴趣的基本问题。最近,将常见变体解释的遗传率分配到基因组区域的贡献引起了很多关注,因为它对理解复杂性状的遗传结构具有重要的应用价值。目前的方法通过联合估计所有区域的贡献来划分总遗传率。然而,当区域数量很大时,这些方法在计算上是难以处理的,并且可能不准确。在本文中,我们提出了一种替代方法,可以将总遗传率划分为任意数量的区域的贡献。我们通过使用模拟证明了我们的方法比当前方法更准确和高效。使用来自人类身高全基因组关联研究的数据集,我们通过估计染色体和亚染色体区域的遗传率贡献来证明我们方法的实用性。