GRCh38 的调节性孟德尔突变得分。

IF 11.8 2区 生物学 Q1 MULTIDISCIPLINARY SCIENCES GigaScience Pub Date : 2022-12-28 Epub Date: 2023-04-21 DOI:10.1093/gigascience/giad024
Max Schubach, Lusiné Nazaretyan, Martin Kircher
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引用次数: 0

摘要

背景:针对罕见孟德尔疾病患者的基因组测序工作增加了对非编码基因组的研究关注,临床上也需要优先考虑可能导致疾病的非编码变异的方法。目前的人类基因组构建(GRCh38)还没有一些用于评估变异致病性和注释的工具,数据库、软件和管道对这些工具的采用也很缓慢:结果:在此,我们介绍了一个更新版的调控孟德尔突变(ReMM)评分,该评分是根据 GRCh38 基因组构建的特征和变异进行重新训练的。与 GRCh37 版本一样,它在高度不平衡的数据上也取得了良好的性能。为了提高可访问性,并为用户提供一个工具箱来对其变异文件进行评分并在基因组中查询分数,我们开发了一个网站和应用程序接口,以方便分数查询:GRCh38 基因组构建版的得分与之前的版本高度相关,由于特征覆盖范围更大,性能也有所提高。在不平衡数据集的非编码突变优先排序方面,ReMM评分的表现比其他变异评分要好得多。文章和网站引用了GRCh37和GRCh38基因组构建版的预评分全基因组文件;UCSC基因组浏览器轨迹和API可在https://remm.bihealth.org。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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The Regulatory Mendelian Mutation score for GRCh38.

Background: Genome sequencing efforts for individuals with rare Mendelian disease have increased the research focus on the noncoding genome and the clinical need for methods that prioritize potentially disease causal noncoding variants. Some tools for assessment of variant pathogenicity as well as annotations are not available for the current human genome build (GRCh38), for which the adoption in databases, software, and pipelines was slow.

Results: Here, we present an updated version of the Regulatory Mendelian Mutation (ReMM) score, retrained on features and variants derived from the GRCh38 genome build. Like its GRCh37 version, it achieves good performance on its highly imbalanced data. To improve accessibility and provide users with a toolbox to score their variant files and look up scores in the genome, we developed a website and API for easy score lookup.

Conclusions: Scores of the GRCh38 genome build are highly correlated to the prior release with a performance increase due to the better coverage of features. For prioritization of noncoding mutations in imbalanced datasets, the ReMM score performed much better than other variation scores. Prescored whole-genome files of GRCh37 and GRCh38 genome builds are cited in the article and the website; UCSC genome browser tracks, and an API are available at https://remm.bihealth.org.

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来源期刊
GigaScience
GigaScience MULTIDISCIPLINARY SCIENCES-
CiteScore
15.50
自引率
1.10%
发文量
119
审稿时长
1 weeks
期刊介绍: GigaScience seeks to transform data dissemination and utilization in the life and biomedical sciences. As an online open-access open-data journal, it specializes in publishing "big-data" studies encompassing various fields. Its scope includes not only "omic" type data and the fields of high-throughput biology currently serviced by large public repositories, but also the growing range of more difficult-to-access data, such as imaging, neuroscience, ecology, cohort data, systems biology and other new types of large-scale shareable data.
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