SingleQ: a comprehensive database of single-cell expression quantitative trait loci (sc-eQTLs) cross human tissues.

IF 3.4 4区生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY

Database: The Journal of Biological Databases and Curation Pub Date : 2024-03-09 DOI:10.1093/database/baae010

Zhiwei Zhou, Jingyi Du, Jianhua Wang, Liangyi Liu, M Gracie Gordon, Chun Jimmie Ye, Joseph E Powell, Mulin Jun Li, Shuquan Rao

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引用次数: 0

Abstract

Mapping of expression quantitative trait loci (eQTLs) and other molecular QTLs can help characterize the modes of action of disease-associated genetic variants. However, current eQTL databases present data from bulk RNA-seq approaches, which cannot shed light on the cell type- and environment-specific regulation of disease-associated genetic variants. Here, we introduce our Single-cell eQTL Interactive Database which collects single-cell eQTL (sc-eQTL) datasets and provides online visualization of sc-eQTLs across different cell types in a user-friendly manner. Although sc-eQTL mapping is still in its early stage, our database curates the most comprehensive summary statistics of sc-eQTLs published to date. sc-eQTL studies have revolutionized our understanding of gene regulation in specific cellular contexts, and we anticipate that our database will further accelerate the research of functional genomics. Database URL: http://www.sqraolab.com/scqtl.

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SingleQ：跨人体组织的单细胞表达定量性状位点（sc-eQTLs）综合数据库。

表达量性状位点（eQTLs）和其他分子 QTLs 的绘图有助于确定疾病相关遗传变异的作用模式。然而，目前的 eQTL 数据库提供的数据来自大量 RNA-seq 方法，无法揭示细胞类型和环境对疾病相关遗传变异的特异性调控。在这里，我们介绍我们的单细胞eQTL互动数据库，该数据库收集单细胞eQTL（sc-eQTL）数据集，并以用户友好的方式提供跨不同细胞类型的sc-eQTL在线可视化。虽然 sc-eQTL 图谱绘制仍处于早期阶段，但我们的数据库收集了迄今为止发表的最全面的 sc-eQTL 统计摘要。sc-eQTL 研究彻底改变了我们对特定细胞环境中基因调控的理解，我们预计我们的数据库将进一步加速功能基因组学的研究。数据库网址：http://www.sqraolab.com/scqtl.

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

Database: The Journal of Biological Databases and Curation MATHEMATICAL & COMPUTATIONAL BIOLOGY-

CiteScore

9.00

自引率

3.40%

发文量

100

审稿时长

>12 weeks

期刊介绍： Huge volumes of primary data are archived in numerous open-access databases, and with new generation technologies becoming more common in laboratories, large datasets will become even more prevalent. The archiving, curation, analysis and interpretation of all of these data are a challenge. Database development and biocuration are at the forefront of the endeavor to make sense of this mounting deluge of data. Database: The Journal of Biological Databases and Curation provides an open access platform for the presentation of novel ideas in database research and biocuration, and aims to help strengthen the bridge between database developers, curators, and users.