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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.
GWAS does not require the identification of the target gene involved in...
Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
Genetic Screens02:46

Genetic Screens

Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which result in visible changes...
Epistasis Analysis01:09

Epistasis Analysis

Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
Pharmacogenetic Phenotypes: Alterations in Pharmacokinetics, Drug Targets and Biologic Milieu01:29

Pharmacogenetic Phenotypes: Alterations in Pharmacokinetics, Drug Targets and Biologic Milieu

Genetic variations significantly influence drug response through pharmacokinetics, receptor interactions, and biologic milieu modifications. Pharmacokinetic alterations impact drug metabolism and clearance, affecting efficacy and toxicity. Variants in drug-metabolizing enzymes, such as CYP2C9 and CYP2C19, alter drug activation and elimination. For example, CYP2C9 loss-of-function variants require lower warfarin doses to prevent excessive bleeding, while CYP2C19 variants reduce clopidogrel...
Multiple Allele Traits01:49

Multiple Allele Traits

The Concept of Multiple Allelism

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Related Experiment Video

Updated: May 8, 2026

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization
08:27

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

Published on: July 27, 2021

An efficient approach to large-scale genotype-phenotype association analyses.

Runqing Yang, Hongwang Li, Lina Fu

    Briefings in Bioinformatics
    |August 31, 2013
    PubMed
    Summary

    This study introduces a novel conditional mapping method for analyzing correlated traits in genetic studies. This approach improves gene mapping accuracy by accounting for trait interdependencies, outperforming traditional single-trait analyses.

    Keywords:
    LASSOconditional phenotypegenotype–phenotype associationlarge-scaleregression analysis

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    Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization
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    Published on: July 27, 2021

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    Infinium Assay for Large-scale SNP Genotyping Applications
    13:33

    Infinium Assay for Large-scale SNP Genotyping Applications

    Published on: November 19, 2013

    Area of Science:

    • Genetics
    • Bioinformatics
    • Statistical Genomics

    Background:

    • Modern biotechnology generates extensive intermediate data (e.g., transcriptional, metabolic products) linking DNA to complex traits.
    • Genome-wide association studies (GWAS) often use regression analysis for quantitative traits, but typically analyze traits individually, ignoring correlations.
    • Existing methods like LASSO (Least Absolute Shrinkage and Selection Operator) efficiently handle single traits but fail to capture inter-trait relationships.

    Purpose of the Study:

    • To develop a novel statistical method for genotype-phenotype association analysis that accounts for correlations among multiple traits.
    • To improve the accuracy of mapping genes associated with quantitative traits by considering their interdependencies.
    • To provide a method for estimating the correlation architecture between traits alongside genetic association analysis.

    Main Methods:

    • Defined a conditional phenotype for each trait, adjusting for other traits in the analysis.
    • Transformed large-scale genotype-phenotype association analyses into analyses of genotype-conditional phenotypes.
    • Utilized shrinkage estimation for each conditional phenotype to simultaneously estimate trait correlations and genetic effects.

    Main Results:

    • The proposed conditional mapping method demonstrated statistical detection power and parameter estimation comparable to joint mapping methods based on multivariate analysis.
    • Simulations confirmed the method's effectiveness in handling correlated quantitative traits.
    • The method was successfully applied to locate expression quantitative trait loci (eQTL) in yeast, demonstrating its practical utility.

    Conclusions:

    • The conditional mapping method offers a robust alternative to traditional trait-by-trait regression and multivariate joint mapping for analyzing correlated traits.
    • This approach enhances the ability to map genes underlying complex traits by effectively incorporating trait correlations.
    • The method provides valuable insights into the genetic architecture and correlation structure of complex traits, as shown in the yeast eQTL study.