4.8 Article

FAVOR: functional annotation of variants online resource and annotator for variation across the human genome

期刊

NUCLEIC ACIDS RESEARCH
卷 51, 期 D1, 页码 D1300-D1311

出版社

OXFORD UNIV PRESS
DOI: 10.1093/nar/gkac966

关键词

-

向作者/读者索取更多资源

Large-scale whole genome sequencing studies are identifying a multitude of genetic variants, and the Functional Annotation of Variants Online Resources (FAVOR) provides a comprehensive platform for annotating and prioritizing these variants based on their functional characteristics. FAVOR allows for online queries and visualization of the findings, making downstream analysis more convenient.
Large biobank-scale whole genome sequencing (WGS) studies are rapidly identifying a multitude of coding and non-coding variants. They provide an unprecedented resource for illuminating the genetic basis of human diseases. Variant functional annotations play a critical role in WGS analysis, result interpretation, and prioritization of disease- or trait-associated causal variants. Existing functional annotation databases have limited scope to perform online queries and functionally annotate the genotype data of large biobank-scale WGS studies. We develop the Functional Annotation of Variants Online Resources (FAVOR) to meet these pressing needs. FAVOR provides a comprehensive multi-faceted variant functional annotation online portal that summarizes and visualizes findings of all possible nine billion single nucleotide variants (SNVs) across the genome. It allows for rapid variant-, gene- and region-level queries of variant functional annotations. FAVOR integrates variant functional information from multiple sources to describe the functional characteristics of variants and facilitates prioritizing plausible causal variants influencing human phenotypes. Furthermore, we provide a scalable annotation tool, FAVORannotator, to functionally annotate large-scale WGS studies and efficiently store the genotype and their variant functional annotation data in a single file using the annotated Genomic Data Structure (aGDS) format, making downstream analysis more convenient.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据