4.7 Article

The Regulatory Mendelian Mutation score for GRCh38

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GIGASCIENCE
卷 12, 期 -, 页码 -

出版社

OXFORD UNIV PRESS
DOI: 10.1093/gigascience/giad024

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variant prediction; machine learning; web service; Mendelian disease; noncoding score; rare variant analysis; imbalanced data

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This study updates the ReMM score for prioritizing noncoding variants in individuals with rare Mendelian disease. The updated version achieves good performance and better coverage of features. A website and API are provided for easy score lookup.
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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