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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: May 8, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

LANTERN: Leveraging Local Ancestry Tracts to Enhance Rare-Variant Aggregate Association Testing.

Yu Wang, Bjoernar Tuftin, Laura M Raffield

Medrxiv : the Preprint Server for Health Sciences

|May 7, 2026

Summary

This summary is machine-generated.

LANTERN is a new method for analyzing rare genetic variants in admixed populations. It enhances association signals by leveraging local ancestry, improving the discovery of disease-related genes in diverse groups.

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Last Updated: May 8, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

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Published on: June 23, 2012

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Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

Area of Science:

Population Genetics
Statistical Genomics
Bioinformatics

Background:

Admixed populations in the Americas are significant. Existing genome-wide association studies (GWAS) methods leverage local ancestry inference for enhanced power and interpretability.
However, methods for rare-variant aggregate association testing in admixed populations are lacking.

Purpose of the Study:

To present LANTERN (Leveraging local ANcestry Tracts to Enhance Rare variaNt aggregate associations), a novel method for rare-variant aggregate association testing in admixed populations.
To demonstrate LANTERN's ability to control Type 1 error and increase power when causal alleles are ancestry-specific.

Main Methods:

LANTERN infers alleles on ancestral haplotypes and performs rare-variant aggregate association testing within a generalized linear mixed model framework.
Method performance was evaluated through simulation studies.
LANTERN was applied to data from African American participants in the Jackson Heart Study.

Main Results:

Simulations showed LANTERN controls Type 1 error and boosts power for detecting associations with ancestry-specific causal alleles.
Application to the Jackson Heart Study identified ancestry-specific rare-variant associations in genes related to red-blood cell (RBC) biology.
A burden of rare alleles on European haplotypes in *EPO* was associated with hemoglobin (HGB) and RBC counts; a burden on African haplotypes in *EPB42* was associated with HGB and RBC.

Conclusions:

LANTERN enables the identification of ancestry-specific rare-variant associations.
The method enhances rare-variant association signals compared to analyses that disregard local ancestry.
LANTERN is implemented in R and available on GitHub.