Computational Assessment of the Expression-modulating Potential for Non-coding Variants

IF 11.5 2区生物学 Q1 GENETICS & HEREDITY

Genomics, Proteomics & Bioinformatics Pub Date : 2023-06-01 DOI:10.1016/j.gpb.2021.10.003

Fang-Yuan Shi , Yu Wang , Dong Huang , Yu Liang , Nan Liang , Xiao-Wei Chen , Ge Gao

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引用次数: 0

Abstract

Large-scale genome-wide association studies (GWAS) and expression quantitative trait locus (eQTL) studies have identified multiple non-coding variants associated with genetic diseases by affecting gene expression. However, pinpointing causal variants effectively and efficiently remains a serious challenge. Here, we developed CARMEN, a novel algorithm to identify functional non-coding expression-modulating variants. Multiple evaluations demonstrated CARMEN’s superior performance over state-of-the-art tools. Applying CARMEN to GWAS and eQTL datasets further pinpointed several causal variants other than the reported lead single-nucleotide polymorphisms (SNPs). CARMEN scales well with the massive datasets, and is available online as a web server at http://carmen.gao-lab.org.

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非编码变异体表达调节潜力的计算评估

大规模的全基因组关联研究（GWAS）和表达量性状位点研究（eQTL）发现了多种通过影响基因表达而与遗传病相关的非编码变异。然而，有效、高效地精确定位因果变异仍然是一个严峻的挑战。在此，我们开发了一种新型算法 CARMEN，用于识别功能性非编码表达调节变异。多项评估表明，CARMEN 的性能优于最先进的工具。将CARMEN应用于GWAS和eQTL数据集，进一步精确定位了除已报道的前导单核苷酸多态性（SNPs）之外的几个因果变异。CARMEN 可以很好地扩展海量数据集，并可作为网络服务器在 http://carmen.gao-lab.org 上在线使用。

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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来源期刊

Genomics, Proteomics & Bioinformatics Biochemistry, Genetics and Molecular Biology-Biochemistry

CiteScore

14.30

自引率

4.20%

发文量

844

审稿时长

61 days

期刊介绍： Genomics, Proteomics and Bioinformatics (GPB) is the official journal of the Beijing Institute of Genomics, Chinese Academy of Sciences / China National Center for Bioinformation and Genetics Society of China. It aims to disseminate new developments in the field of omics and bioinformatics, publish high-quality discoveries quickly, and promote open access and online publication. GPB welcomes submissions in all areas of life science, biology, and biomedicine, with a focus on large data acquisition, analysis, and curation. Manuscripts covering omics and related bioinformatics topics are particularly encouraged. GPB is indexed/abstracted by PubMed/MEDLINE, PubMed Central, Scopus, BIOSIS Previews, Chemical Abstracts, CSCD, among others.