在世代研究中对基因组新生儿查的变异优先级策略的评估
Joanna Kaplanis1, Dasha Deen1, Prasanth Sivakumar1
1Genomics England, London, United Kingdom.
概括
这项研究引入了一种自动化方法,通过新生儿基因组测序来优先考虑通过新生儿基因组测序发现的遗传变异. 目标是减少错误阳性,确保对临床使用的罕见遗传疾病的准确识别.
科学领域:
- 基因组学就是基因组学.
- 临床遗传学 临床遗传学
- 生物信息学是一种生物信息学.
背景情况:
- 基因组测序可以识别新生儿的许多罕见遗传疾病.
- 尽量减少错误阳性并最大限度地提高临床效用对于有效的新生儿查至关重要.
- 该研究旨在调查英格兰10万名新生儿的基因组测序.
研究的目的:
- 开发和评估用于新生儿基因组测序的自动化变异优先级方法.
- 为了减少假阳性结果,同时保持高临床效用.
- 为了确保优先选择的变种经过临床专家严格的手动审查.
主要方法:
- 评估特异性使用34,410个未对罕见疾病进行丰富的样本.
- 使用546个已知诊断变异与新生儿查相关的样本评估灵敏度.
- 使用覆盖范围和副本编号变种可调用度量用于变种检测.
主要成果:
- 估计3-5%的样本将产生优先考虑的变体,需要手动审查.
- 预计<1%的病例将具有需要进一步确认的可报告变异.
- 在一代研究中,对基因的估计灵敏度约为80%.
结论:
- 对变异优先级的基因特异性评估至关重要.
- 建立分析有效性是将基因组测序纳入新生儿查计划的先决条件.
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