文学挖掘工具对变体分类的比较:通过50个RYR1变体的镜头
Zara Wermers1, Seeley Yoo1, Bailey Radenbaugh1
1Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD.
概括
识别相关的变异文献对于分类致病性至关重要. 一项研究发现,使用多个文献挖掘工具是必要的,因为没有一个工具可以完全检索出所有相关出版物用于变种策划.
科学领域:
- 遗传学和基因组学 遗传学和基因组学
- 分子病理学分子病理学
- 生物信息学是一种生物信息学.
背景情况:
- 变异性致病性分类依赖于系统的方案.
- 人口频率数据 (gnomAD) 和生物信息预测器 (ClinGen) 是已知的资源.
- 在识别变种特定文献的共识来源中存在差距.
研究的目的:
- 评估四种文献挖掘工具对变异确定性的实用性.
- 为讨论这些工具在识别相关变体文献方面的有效性提供信息.
主要方法:
- 评估了四种文献挖掘工具 (人类基因突变数据库,大脑,ClinVar,LitVar 2.0) 进行了评估.
- 确定了50个RYR1变体的相关文献.
- 确定了每个工具的灵敏度和精度.
主要成果:
- 各种工具的灵敏度在0.332到0.687.7之间.
- 精度在0.389和0.906.6之间变化.
- 没有单一的工具能够识别出测试变体的所有相关出版物.
结论:
- 目前,对变异策划进行全面的文献搜索需要使用多种工具.
- 结合各种文献挖掘工具的结果,提高了变体相关信息的完整性.
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