, Prague, Czech Republic.
Radboudumc, Nijmegen, The Netherlands.
Methods Mol Biol. 2021;2212:69-92. doi: 10.1007/978-1-0716-0947-7_6.
Undiscovered gene-to-gene interaction (epistasis) is a possible explanation for the "missing heritability" of complex traits and diseases. On a genome-wide scale, screening for epistatic effects among all possible pairs of genetic markers faces two main complications. Firstly, the classical statistical methods for modeling epistasis are computationally very expensive, which makes them impractical on such large scale. Secondly, straightforward corrections for multiple testing using the classical methods tend to be too coarse and inefficient at discovering the epistatic effects in such a large scale application. In this chapter, we describe both the underlying framework and practical examples of two-stage statistical testing methods that alleviate both of the aforementioned complications.
未被发现的基因-基因相互作用（上位性）是复杂性状和疾病“遗传缺失”的一个可能解释。在全基因组范围内，筛选所有可能的遗传标记对之间的上位性效应面临两个主要的复杂性。首先，用于建模上位性的经典统计方法在计算上非常昂贵，这使得它们在如此大的规模上不切实际。其次，使用经典方法进行多重检验的直接校正往往过于粗糙，在如此大规模的应用中发现上位性效应的效率也很低。在本章中，我们描述了缓解上述两个复杂性的两阶段统计检验方法的基本框架和实际例子。
