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Genome-wide Association Studies-GWAS01:11

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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.
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Human genetics provides a profound framework for understanding the interplay between genetic predispositions and human psychology. At the heart of this discipline lies the study of how genes influence physical traits, behaviors, and susceptibility to diseases. Each person carries a unique genetic code that subtly or significantly shapes their psychological and behavioral landscape.
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Infinium Assay for Large-scale SNP Genotyping Applications
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Haplotype reference consortium panel: Practical implications of imputations with large reference panels.

Adriana I Iglesias1,2, Sven J van der Lee1, Pieter W M Bonnemaijer1,2

  • 1Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands.

Human Mutation
|May 12, 2017
PubMed
Summary
This summary is machine-generated.

The Haplotype Reference Consortium (HRC) panel improves genetic variant imputation accuracy, especially for rare variants. This enhanced imputation led to better glaucoma-associated gene discovery in a large genome-wide association study.

Keywords:
1000 Genomes Project reference panelHaplotype Reference Consortiumassociation studiesimputationvertical cup-disc ratio

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Area of Science:

  • Genetics
  • Genomics
  • Bioinformatics

Background:

  • Accurate imputation of genetic variants is crucial for large-scale genetic studies.
  • The Haplotype Reference Consortium (HRC) provides a large, high-quality imputation panel.
  • Previous imputation panels, like the 1000 Genomes Project (1000GP), have limitations in variant coverage.

Purpose of the Study:

  • To evaluate the accuracy of genetic variant imputation using the HRC panel compared to the 1000GP panel.
  • To assess the impact of HRC imputation on a genome-wide association meta-analysis for the vertical cup-to-disc ratio, a glaucoma endophenotype.

Main Methods:

  • Directly genotyped exome array data were compared with imputed genotypes from both 1000GP and HRC panels.
  • A genome-wide association meta-analysis was conducted on vertical cup-to-disc ratio data from four cohorts using both 1000GP and HRC imputations.

Main Results:

  • HRC imputation demonstrated improved concordance between assayed and imputed genotypes, particularly for low-frequency variants.
  • The meta-analysis using HRC imputation yielded significantly improved P-values compared to the 1000GP-based analysis.
  • Eight genome-wide significant loci were identified using HRC imputation versus seven using 1000GP imputation, despite identical sample sizes.

Conclusions:

  • The HRC imputation panel offers enhanced accuracy for genetic variant imputation.
  • Utilizing the HRC panel can improve the power and resolution of genome-wide association studies, facilitating gene discovery and fine-mapping for complex traits like glaucoma.