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a catalog of biological databases

e.g., animal; RNA; Methylation; China

Database Profile

General information

Full name: Cell type-Specific Enrichment Analysis DataBase
Description: An omnibus for human complex trait and cell type associations
Year founded: 2021
Last update:
Real time : Checking...
Country/Region: United States
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Contact information

University/Institution: The University of Texas Health Science Center
Address: The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
Country/Region: United States
Contact name (PI/Team): Zhongming Zhao
Contact email (PI/Helpdesk):


CSEA-DB: an omnibus for human complex trait and cell type associations. [PMID: 33211888]
Dai Y, Hu R, Manuel AM, Liu A, Jia P, Zhao Z.

During the past decade, genome-wide association studies (GWAS) have identified many genetic variants with susceptibility to several thousands of complex diseases or traits. The genetic regulation of gene expression is highly tissue-specific and cell type-specific. Recently, single-cell technology has paved the way to dissect cellular heterogeneity in human tissues. Here, we present a reference database for GWAS trait-associated cell type-specificity, named Cell type-Specific Enrichment Analysis DataBase (CSEA-DB, available at Specifically, we curated total of 5120 GWAS summary statistics data for a wide range of human traits and diseases followed by rigorous quality control. We further collected >900 000 cells from the leading consortia such as Human Cell Landscape, Human Cell Atlas, and extensive literature mining, including 752 tissue cell types from 71 adult and fetal tissues across 11 human organ systems. The tissues and cell types were annotated with Uberon and Cell Ontology. By applying our deTS algorithm, we conducted 10 250 480 times of trait-cell type associations, reporting a total of 598 (11.68%) GWAS traits with at least one significantly associated cell type. In summary, CSEA-DB could serve as a repository of association map for human complex traits and their underlying cell types, manually curated GWAS, and single-cell transcriptome resources.

Nucleic Acids Res. 2021:49(D1) | 2 Citations (from Europe PMC, 2021-11-27)


All databases:
2922/5113 (42.871%)
488/783 (37.803%)
Health and medicine:
623/1093 (43.092%)
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Created on: 2021-11-15
Curated by:
lin liu [2021-11-15]