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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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Updated: Jun 30, 2025

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Subset-based method for cross-tissue transcriptome-wide association studies improves power and interpretability.

Xinyu Guo¹, Nilanjan Chatterjee², Diptavo Dutta³

¹Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90007, USA.

|March 16, 2024

Summary

This summary is machine-generated.

This study introduces a new method, Cross-Tissue Subset-based Transcriptome-Wide Association Study (CSTWAS), to improve the identification of gene-trait associations by analyzing gene expression across multiple tissues. CSTWAS enhances statistical power and pinpoints specific tissues involved in complex traits.

Keywords:

GWAS summary statistics TWAS associated-tissue cross-tissue gene-based test meta analysis

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Last Updated: Jun 30, 2025

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Area of Science:

Genetics
Bioinformatics
Systems Biology

Background:

Genome-wide association studies (GWASs) combined with molecular phenotypes like gene expression enhance understanding of genetic variants.
Existing methods for gene-trait association, often based on gene expression imputation and meta-analysis across tissues, have limitations in detecting weaker associations or identifying specific active tissues.

Conclusions:

CSTWAS is an effective meta-analysis tool for identifying gene-trait associations by leveraging cross-tissue expression data.
Application to complex traits revealed biologically meaningful signals and provided insights into disease etiology through the identification of associated tissue sets.