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xQTL图谱:人类细胞分辨率多组学遗传调控景观的综合资源。

xQTLatlas: a comprehensive resource for human cellular-resolution multi-omics genetic regulatory landscape.

作者信息

Jia Yuran, Dong Hongchao, Li Linhao, Wang Fang, Juan Liran, Wang Yadong, Guo Hongzhe, Zhao Tianyi

机构信息

Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China.

School of Medicine and Health, Harbin Institute of Technology, Harbin 150001, China.

出版信息

Nucleic Acids Res. 2025 Jan 6;53(D1):D1270-D1277. doi: 10.1093/nar/gkae837.

Abstract

Understanding how genetic variants influence molecular phenotypes in different cellular contexts is crucial for elucidating the molecular and cellular mechanisms behind complex traits, which in turn has spurred significant advances in research into molecular quantitative trait locus (xQTL) at the cellular level. With the rapid proliferation of data, there is a critical need for a comprehensive and accessible platform to integrate this information. To meet this need, we developed xQTLatlas (http://www.hitxqtl.org.cn/), a database that provides a multi-omics genetic regulatory landscape at cellular resolution. xQTLatlas compiles xQTL summary statistics from 151 cell types and 339 cell states across 55 human tissues. It organizes these data into 20 xQTL types, based on four distinct discovery strategies, and spans 13 molecular phenotypes. Each entry in xQTLatlas is meticulously annotated with comprehensive metadata, including the origin of the tissue, cell type, cell state and the QTL discovery strategies utilized. Additionally, xQTLatlas features multiscale data exploration tools and a suite of interactive visualizations, facilitating in-depth analysis of cell-level xQTL. xQTLatlas provides a valuable resource for deepening our understanding of the impact of functional variants on molecular phenotypes in different cellular environments, thereby facilitating extensive research efforts.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca8c/11701524/5434d33fa9e7/gkae837figgra1.jpg

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