With the development of next-generation sequencing technology, de novo variants (DNVs) with deleterious effects can be identified and investigated for their effects on birth defects such as congenital heart disease (CHD). However, statistical power is still limited for such studies because of the small sample size due to the high cost of recruiting and sequencing samples and the low occurrence of DNVs. DNV analysis is further complicated by genetic heterogeneity across diseased individuals. Therefore, it is critical to jointly analyze DNVs with other types of genomic/biological information to improve statistical power to identify genes associated with birth defects. In this review, we discuss the general workflow, recent developments in statistical methods, and future directions for DNV analysis.

中文翻译：

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评估新生变异对出生缺陷影响的统计方法

随着下一代测序技术的发展，具有有害影响的从头变异（DNV）可以被识别并研究其对先天性心脏病（CHD）等出生缺陷的影响。然而，由于样本招募和测序成本高昂以及 DNV 发生率低而导致样本量较小，此类研究的统计功效仍然有限。由于患病个体之间的遗传异质性，DNV 分析变得更加复杂。因此，将 DNV 与其他类型的基因组/生物信息联合分析，以提高识别与出生缺陷相关基因的统计能力至关重要。在这篇综述中，我们讨论了 DNV 分析的一般工作流程、统计方法的最新发展以及未来的方向。