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Related Concept Videos

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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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

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

Published on: June 21, 2018

Candidate gene association studies.

M Dawn Teare1

  • 1Health Services Research, School of Health and Related Research, University of Sheffield, Sheffield, UK.

Methods in Molecular Biology (Clifton, N.J.)
|December 15, 2010
PubMed
Summary
This summary is machine-generated.

Candidate gene association studies investigate links between genetic variations and traits. This chapter details methods for analyzing associations with specific phenotypes, focusing on single or few genetic loci.

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

Published on: July 27, 2021

Area of Science:

  • Genetics
  • Biostatistics
  • Human Genetics

Background:

  • Candidate gene association studies (CGAS) explore the relationship between specific genetic variations and observable traits (phenotypes).
  • Phenotypes can be quantitative (e.g., height) or binary (e.g., presence/absence of disease).
  • Effect sizes are measured differently based on phenotype type, using genotype-specific means or per-allele effects for quantitative traits, and genotype-specific risk or relative risk for binary traits.

Purpose of the Study:

  • To outline methodologies for candidate gene association studies.
  • To focus on the investigation of associations between a single or small number of genetic loci and specific phenotypes.
  • To provide a methodological overview for researchers in the field.

Main Methods:

  • Focus on statistical approaches for analyzing genetic association data.
  • Discuss methods for calculating effect sizes for both quantitative and binary phenotypes.
  • Detail techniques applicable when investigating a limited number of genetic loci.

Main Results:

  • The chapter emphasizes the methodological aspects of candidate gene association studies.
  • It highlights the importance of appropriate statistical measures for different phenotype types.
  • The focus remains on the practical application of these methods in genetic research.

Conclusions:

  • Candidate gene association studies are crucial for understanding the genetic basis of phenotypes.
  • Methodological rigor is essential for accurately characterizing genetic associations.
  • This chapter provides a focused guide to the methodology for investigating single or few genetic loci.