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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...
Human Genetics01:28

Human Genetics

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.
The complex relationship between genetics and psychology is observable through common biological components such...
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...
Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

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,...
DNA Microarrays02:34

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
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...

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Related Experiment Video

Updated: Jun 17, 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

Genome-wide gene-based association study.

Hsin-Chou Yang1, Yu-Jen Liang, Chia-Min Chung

  • 1Institute of Statistical Science, Academia Sinica, Number 128, Section 2, Academia Road, Nankang, Taipei 115, Taiwan, Republic of China. hsinchou@stat.sinica.edu.tw.

BMC Proceedings
|December 19, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces a novel two-stage genome-wide association scanning method for identifying rheumatoid arthritis susceptibility genes. The approach effectively detects minor-effect genes and confirms known associations, highlighting the major histocompatibility complex region.

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Area of Science:

  • Genetics and Genomics
  • Computational Biology
  • Rheumatology

Background:

  • Genome-wide association studies (GWAS) are crucial for identifying disease susceptibility genes but face computational and modeling challenges.
  • Existing methods for analyzing single-nucleotide polymorphisms (SNPs) can be complex and may struggle with minor-effect genes or multiple testing.
  • Rheumatoid arthritis (RA) is a complex autoimmune disease with a significant genetic component requiring advanced analytical approaches.

Purpose of the Study:

  • To propose and evaluate a novel two-stage genome-wide association scanning procedure for RA genetics.
  • To enhance the detection of genes associated with rheumatoid arthritis, including those with minor effects.
  • To simplify interpretation and alleviate multiple-testing burdens in genetic association studies.

Main Methods:

  • A two-stage approach combining single-locus (exact Armitage trend test or logistic regression) and gene-based (p-value combination) association scans.
  • Application of the method to the Genetic Analysis Workshop 16 Problem 1 rheumatoid arthritis dataset.
  • Comparison with existing single-locus and multi-locus methods to assess advantages.

Main Results:

  • The proposed method identified strong association signals within the human major histocompatibility complex (MHC) region, confirming its importance in RA.
  • Previously reported RA-associated genes (PTPN22, C5, IL2RB) were confirmed.
  • Novel candidate RA-associated genes, including HLA-DRA, BTNL2, C6orf10, NOTCH4, TAP2, and TNXB, were identified.

Conclusions:

  • The developed two-stage GWAS procedure is effective for identifying RA susceptibility genes, offering convenience in defining regions and interpreting results.
  • The method demonstrates power in detecting minor-effect genes and helps manage the multiple-testing problem.
  • The study reinforces the critical role of the MHC region in rheumatoid arthritis and identifies novel candidate genes for further investigation.