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A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
Published on: August 16, 2017
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WebCSEA: web-based cell-type-specific enrichment analysis of genes.
Yulin Dai1, Ruifeng Hu1,2,3, Andi Liu1,4
1Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
Nucleic Acids Research
|May 24, 2022
Summary
This study introduces WebCSEA, a tool for analyzing gene cell-type specificity in human tissues. It helps researchers understand how genes relate to complex traits and diseases across different cell types.
Area of Science:
- Genomics
- Bioinformatics
- Human Physiology
Background:
- Human complex traits and diseases exhibit tissue- and cell-type-specific patterns.
- Single-cell RNA sequencing (scRNA-seq) reveals cellular heterogeneity, enabling context-specific gene expression studies.
- Understanding gene-tissue-cell type (TC) specificity is crucial for disease research.
Purpose of the Study:
- To present the first web-based application, WebCSEA, for assessing gene cell-type specificity.
- To provide a comprehensive resource for exploring TC-specificity across human tissues.
- To facilitate the understanding of complex trait-associated gene expression in specific human TCs.
Main Methods:
- Curated 111 scRNA-seq human tissue panels and 1,355 TCs from 61 tissues.
- Adapted the decoding tissue-specificity (deTS) algorithm to measure TC enrichment.
- Developed a permutation-based method to estimate TC-specificity and overcome signature gene bias.
Main Results:
- WebCSEA offers a user-friendly platform for analyzing gene TC-specificity.
- The application visualizes cell-type specificity across 1,355 human TCs via interactive heatmaps.
- Provides interactive and static visualizations stratified by organ system, developmental stage, and top TCs.
Conclusions:
- WebCSEA is a valuable one-click tool for comprehensive exploration of gene TC-specificity.
- It aids in understanding the cellular context of gene function in human health and disease.
- The application supports research into the genetic basis of complex traits and common diseases.

