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scQTLbase:一个整合的人类单细胞 eQTL 数据库。

scQTLbase: an integrated human single-cell eQTL database.

机构信息

Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518055, China.

School of Public Health, Health Science Center, Ningbo University, Ningbo 315211, China.

出版信息

Nucleic Acids Res. 2024 Jan 5;52(D1):D1010-D1017. doi: 10.1093/nar/gkad781.

Abstract

Genome-wide association studies (GWAS) have identified numerous genetic variants associated with diseases and traits. However, the functional interpretation of these variants remains challenging. Expression quantitative trait loci (eQTLs) have been widely used to identify mutations linked to disease, yet they explain only 20-50% of disease-related variants. Single-cell eQTLs (sc-eQTLs) studies provide an immense opportunity to identify new disease risk genes with expanded eQTL scales and transcriptional regulation at a much finer resolution. However, there is no comprehensive database dedicated to single-cell eQTLs that users can use to search, analyse and visualize them. Therefore, we developed the scQTLbase (http://bioinfo.szbl.ac.cn/scQTLbase), the first integrated human sc-eQTLs portal, featuring 304 datasets spanning 57 cell types and 95 cell states. It contains ∼16 million SNPs significantly associated with cell-type/state gene expression and ∼0.69 million disease-associated sc-eQTLs from 3 333 traits/diseases. In addition, scQTLbase offers sc-eQTL search, gene expression visualization in UMAP plots, a genome browser, and colocalization visualization based on the GWAS dataset of interest. scQTLbase provides a one-stop portal for sc-eQTLs that will significantly advance the discovery of disease susceptibility genes.

摘要

全基因组关联研究 (GWAS) 已经鉴定出许多与疾病和特征相关的遗传变异。然而,这些变异的功能解释仍然具有挑战性。表达数量性状基因座 (eQTLs) 已被广泛用于鉴定与疾病相关的突变,但它们只能解释 20-50%的与疾病相关的变异。单细胞 eQTLs (sc-eQTLs) 研究为识别新的疾病风险基因提供了巨大的机会,可扩大 eQTL 规模,并以更精细的分辨率进行转录调控。然而,目前还没有专门用于单细胞 eQTLs 的综合数据库,用户可以使用该数据库进行搜索、分析和可视化。因此,我们开发了 scQTLbase(http://bioinfo.szbl.ac.cn/scQTLbase),这是第一个集成的人类 sc-eQTLs 门户,涵盖了 57 种细胞类型和 95 种细胞状态的 304 个数据集。它包含约 1600 万个与细胞类型/状态基因表达显著相关的 SNPs 和来自 3333 个特征/疾病的约 0.69 万个疾病相关的 sc-eQTLs。此外,scQTLbase 提供了 sc-eQTL 搜索、UMAP 图中的基因表达可视化、基因组浏览器以及基于感兴趣的 GWAS 数据集的共定位可视化。scQTLbase 为 sc-eQTLs 提供了一站式门户,将极大地推动疾病易感性基因的发现。

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