Traditionally, heritability has been estimated using family-based methods such as twin studies. Advancements in molecular genomics have facilitated the development of alternative methods that utilise large samples of unrelated or related individuals. Yet, specific challenges persist in the estimation of heritability such as epistasis, assortative mating and indirect genetic effects. Here, we provide an overview of common methods applied in genetic epidemiology to estimate heritability i.e., the proportion of phenotypic variation explained by genetic variation. We provide a guide to key genetic concepts required to understand heritability estimation methods from family-based designs (twin and family studies), genomic designs based on unrelated individuals (LD score regression, GREML), and family-based genomic designs (Sibling regression, GREML-KIN, Trio-GCTA, MGCTA, RDR). For each method, we describe how heritability is estimated, the assumptions underlying its estimation, and discuss the implications when these assumptions are not met. We further discuss the benefits and limitations of estimating heritability within samples of unrelated individuals compared to samples of related individuals. Overall, this article is intended to help the reader determine the circumstances when each method would be appropriate and why.

翻译：分子基因组学的进步促进了替代方法的开发,这些方法利用了不相干或相关个人的大量样本;然而,在估计遗传性方面仍然存在具体的挑战,例如粘附性、血清交配和间接遗传效应。这里,我们概述了遗传流行病学中用来估计遗传性的共同方法,即遗传变异所解释的胎儿变异比例。我们为关键遗传概念提供了指南,以了解基于家庭的设计(双胞胎和家庭研究)、基于无关个人的基因组设计(LD评分回归、GREML)和基于家庭的基因组设计(Sibling Regain、GREM-KIN、Trio-GCTA、MGCTA、RDR)的遗传性估计方法,以估计遗传性,即遗传变异所解释的胎儿变异比例。我们进一步讨论了在非家庭设计(双胞胎和家庭研究)、基于无关个人的基因组图案(LD分回归、GREML)和基于家庭的基因组图案的设计(Sibling returing)的遗传图案设计(Simmediction-KIN、Grio-GCTAT、MTA、MTrio-MT、MT、MT、MT、MIT、MT、MTT、RDRDR、R、R、R、R、R)中估计其估计其估计的可乘的个人的遗传学、以及这些假设不相联。我们说明这些假设不满足的假设的假设的假设的利和影响。我们进一步讨论性评估的利和局限性。