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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

Updated: Mar 14, 2026

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

scTWAS: a powerful statistical framework for single-cell transcriptome-wide association studies.

Zhaotong Lin¹, Chang Su^2,3

¹Department of Statistics, Florida State University, Tallahassee, FL, USA.

Nature Communications

|March 13, 2026

Summary

This summary is machine-generated.

This study introduces scTWAS, a new method for cell-type-specific transcriptome-wide association studies (TWAS) using single-cell data. scTWAS enhances the identification of gene-trait associations, particularly in complex diseases like Alzheimer's.

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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

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Last Updated: Mar 14, 2026

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq

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Published on: October 31, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

Area of Science:

Genomics
Computational Biology
Statistical Genetics

Background:

Bulk RNA sequencing aggregates cell signals, limiting cell-type-specific genetic association studies.
Single-cell RNA sequencing (scRNA-seq) offers cell-type resolution but presents data challenges (noise, sparsity).

Purpose of the Study:

To develop a statistical method (scTWAS) for cell-type-specific transcriptome-wide association studies (TWAS) using scRNA-seq data.
To address the unique challenges posed by noisy and sparse single-cell gene expression data.

Main Methods:

Proposed scTWAS, a novel statistical method utilizing a latent-variable model and moment-based estimation.
Applied scTWAS to population-scale single-cell RNA sequencing datasets from blood and brain tissues.

Main Results:

scTWAS demonstrated improved prediction of genetically regulated gene expression across diverse cell types.
Identified significantly more gene-trait associations for hematological and immune-related traits compared to existing methods.
Revealed cell-subtype-specific associations for Alzheimer's disease, implicating specific genes in distinct microglial subtypes.

Conclusions:

scTWAS effectively overcomes challenges in single-cell data for cell-type-specific TWAS.
Provides a powerful tool for discovering cell-type-specific genetic contributions to complex traits and diseases.
Advances understanding of disease mechanisms at a granular cellular level.