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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...
Multiple Allele Traits01:49

Multiple Allele Traits

The Concept of Multiple Allelism
Multiple Allele Traits01:49

Multiple Allele Traits

The Concept of Multiple Allelism
Polygenic Traits01:18

Polygenic Traits

When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
Polygenic Traits01:18

Polygenic Traits

When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
Behavioral Genetics and Its Designs01:23

Behavioral Genetics and Its Designs

Behavior genetics explores how genetic inheritance influences human behavior. It focuses on how genes, passed from parents to offspring, contribute to the development of behavioral traits and tendencies. This branch of genetics seeks to understand the complex interplay between inherited genetic factors and environmental influences in shaping our behaviors.
The primary methodologies used in behavior genetics include family studies, twin studies, and adoption studies, each providing unique...

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Related Experiment Video

Updated: Jun 20, 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

Regression-based approach for testing the association between multi-region haplotype configuration and complex trait.

Yanling Hu1, Sinnwell Jason, Qishan Wang

  • 1School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, PR China. ylhu0323@sjtu.edu.cn

BMC Genetics
|September 19, 2009
PubMed
Summary

This study introduces a new regression method to analyze genetic interactions across multiple unlinked genomic regions. The approach effectively identifies complex trait associations and outperforms existing methods.

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

Published on: June 21, 2018

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Last Updated: Jun 20, 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

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

Area of Science:

  • Genetics
  • Statistical Genomics
  • Bioinformatics

Background:

  • Complex traits are often influenced by numerous genes and their interactions.
  • Simultaneously analyzing multiple, unlinked genomic regions is crucial for understanding these complex genetic architectures.

Purpose of the Study:

  • To develop a novel regression-based approach for assessing haplotype interactions between different unlinked genomic regions.
  • To provide a statistically robust method for testing the null hypothesis of non-genetic association in complex traits.

Main Methods:

  • Developed a regression-based framework to evaluate interactions among haplotypes from unlinked regions.
  • Employed score statistics for hypothesis testing and the minP approach for multiple testing correction.
  • Utilized Monte-Carlo simulations to correct P values for the optimal multi-region, multi-marker configuration.

Main Results:

  • Simulation studies demonstrated the validity and power of the proposed method in detecting haplotype interaction associations.
  • The approach successfully assessed interactions between multiple markers within each unlinked region.

Conclusions:

  • The developed methods are as powerful, or more so, than existing tools like htr and hapcc for binary traits without covariates.
  • The model accommodates a broader range of traits and allows for covariate adjustments.
  • Applied to analyze associations between four unlinked genes and pig meat quality, demonstrating practical utility.