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Genome-wide Association Studies-GWAS

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...

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Related Experiment Video

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Single-cell RNA-Seq of Defined Subsets of Retinal Ganglion Cells

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Published on: May 22, 2017

A statistical framework to identify cell types whose genetically regulated proportions are associated with complex

Wei Liu¹, Wenxuan Deng², Ming Chen²

¹Program of Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America.

|July 31, 2023

Summary

This study introduces cell-type Wide Association Study (cWAS), a new method linking genetic data and cell proportions to disease risk. cWAS identifies specific cell types associated with complex diseases, aiding biomarker discovery.

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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

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Area of Science:

Genomics and Bioinformatics
Computational Biology
Disease Association Studies

Background:

Identifying disease-relevant tissues and cell types is crucial for understanding gene function and variant impact.
Cell type proportions are emerging as potential biomarkers for disease prediction.

Purpose of the Study:

To introduce a novel statistical framework, cell-type Wide Association Study (cWAS).
To integrate genetic and transcriptomics data for identifying cell types with genetically regulated proportions (GRPs) associated with diseases or traits.

Main Methods:

Developed and applied the cell-type Wide Association Study (cWAS) framework.
Integrated genetic data with transcriptomics data.
Utilized simulated and real genome-wide association study (GWAS) data.

Main Results:

cWAS demonstrated good statistical power in identifying significant GRP associations in disease-associated tissues.
Found associations between endothelial cell GRPs and Idiopathic Pulmonary Fibrosis in lung tissue.
Linked myofibroblast GRPs in lung tissue to Chronic Obstructive Pulmonary Disease.
Identified a negative association between blood CD8+ T cell GRPs and breast cancer risk and survival.

Conclusions:

cWAS is an effective tool for discovering cell types associated with complex diseases through GRPs.
The findings highlight the role of specific cell type proportions in the etiology of pulmonary diseases and breast cancer.