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Genome-wide Association Studies-GWAS01:11

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.
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A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
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Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
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A genotype-based approach to assessing the association between single nucleotide polymorphisms.

Stefan Wellek1, Andreas Ziegler

  • 1Division of Biostatistics, Central Institute of Mental Health, Mannheim/University of Heidelberg, Mannheim, Germany.

Human Heredity
|December 17, 2008
PubMed
Summary

This study introduces a genotype-based measure for estimating linkage disequilibrium (LD) between single nucleotide polymorphisms (SNPs). This new method, Pearson

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Area of Science:

  • Genetics
  • Bioinformatics
  • Statistical genomics

Background:

  • Linkage disequilibrium (LD) measurement is crucial for genetic association studies.
  • Existing LD measures often rely on haplotype data, requiring Hardy-Weinberg equilibrium (HWE) assumptions when family data is absent.
  • Haplotype estimation introduces potential inaccuracies.

Purpose of the Study:

  • To propose and validate a genotype-based measure for estimating LD between single nucleotide polymorphisms (SNPs).
  • To ensure the proposed LD measure is invariant under the transition from haplotypes to diploid genotypes when HWE holds.
  • To compare the performance of the genotype-based measure against traditional haplotype-based methods.

Main Methods:

  • Developed a genotype-based LD measure using Pearson's correlation coefficient (rho).
  • Derived the asymptotic distribution of the empirical product-moment correlation (R) for counting variables.
  • Constructed asymptotically valid confidence intervals using Fisher's z-transformation.
  • Validated the approach through numerical studies and application to IL-4 receptor gene (IL4R) polymorphism data.

Main Results:

  • Pearson's rho demonstrates invariance from haplotypes to diploid genotypes under HWE, unlike other measures like Lewontin's D'.
  • The proposed genotype-based LD estimation shows negligible loss in precision compared to haplotype-based methods.
  • Asymptotically valid confidence intervals for LD were constructed.

Conclusions:

  • A robust genotype-based LD measure is presented, simplifying association studies by avoiding haplotype estimation.
  • The method is statistically sound and practically applicable, offering a viable alternative to haplotype-based approaches.
  • This approach enhances the efficiency and accuracy of genetic association studies, particularly for the IL-4 receptor gene.