Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

14.8K
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...
14.8K
Behavioral Genetics and Its Designs01:23

Behavioral Genetics and Its Designs

726
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...
726
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

154
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
154
Biostatistics: Overview01:20

Biostatistics: Overview

450
Biostatistics plays a crucial role in understanding and analyzing data in healthcare and biology. Biostatisticians conduct experiments, gather evidence, and draw meaningful conclusions using statistical methods and techniques. Different variables form the foundation of biostatistical analysis, allowing researchers to understand and interpret data effectively. These variables are classified into different types, each serving a specific purpose in statistical analysis.
Discrete variables are...
450
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

6.5K
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
6.5K
Hardy-Weinberg Principle01:49

Hardy-Weinberg Principle

74.9K
Diploid organisms have two alleles of each gene, one from each parent, in their somatic cells. Therefore, each individual contributes two alleles to the gene pool of the population. The gene pool of a population is the sum of every allele of all genes within that population and has some degree of variation. Genetic variation is typically expressed as a relative frequency, which is the percentage of the total population that has a given allele, genotype or phenotype.
74.9K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Evaluating the impact of conditional micro-incentives on linkage to HIV care in rural South Africa: Results from the Home-Based Intervention to Test and Start (HITS) trial.

Health policy and planning·2026
Same author

A joint model for a longitudinal outcome and a progressive multistate model under a mixed observation scheme.

Statistical methods in medical research·2026
Same author

Late Preschool BMI Acceleration as the Strongest Predictor of Childhood Cardiometabolic Risk at School Entry: A Dual-Trajectory Cohort Study.

Diabetes, metabolic syndrome and obesity : targets and therapy·2026
Same author

Dual inhibition of glycolysis and epigenetics via a nanodelivery system for colorectal cancer treatment.

Nanomedicine : nanotechnology, biology, and medicine·2026
Same author

IMPERATIVE: Harnessing male peer networks to enhance engagement with HIV prevention: A large-scale cluster randomised trial to increase HIV self-testing and PrEP uptake among men in Eastern Zimbabwe.

Research square·2026
Same author

Unconventional Room-Temperature Antisymmetric Magnetoresistance in van der Waals Fe<sub>3</sub>GaTe<sub>2</sub>/Pt Heterostructures.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026

Related Experiment Video

Updated: Nov 8, 2025

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
12:39

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

11.5K

A BAYESIAN GRAPHICAL MODEL FOR GENOME-WIDE ASSOCIATION STUDIES (GWAS).

Laurent Briollais1,2, Adrian Dobra3, Jinnan Liu1

  • 1Lunenfeld-Tanenbaum Research Institute.

The Annals of Applied Statistics
|April 28, 2021
PubMed
Summary

This study introduces a novel Bayesian graphical model for multi-single nucleotide polymorphism (SNP) analysis in genome-wide association studies (GWAS). The new framework enhances the detection of complex genetic associations for human diseases.

Keywords:
BayesianGWASGraphical modelSNPbreast cancerstochastic search

More Related Videos

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

4.5K
A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
05:01

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

Published on: July 1, 2020

3.5K

Related Experiment Videos

Last Updated: Nov 8, 2025

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
12:39

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

11.5K
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

4.5K
A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
05:01

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

Published on: July 1, 2020

3.5K

Area of Science:

  • Genetics
  • Statistical genetics
  • Computational biology

Background:

  • Genome-wide association studies (GWAS) traditionally use simple models that limit the understanding of complex human disease genetics.
  • Existing methods struggle to capture the intricate genetic architecture involving multiple single nucleotide polymorphisms (SNPs).

Purpose of the Study:

  • To develop a general statistical framework for multi-SNP analysis of GWAS data using a Bayesian graphical model.
  • To enable the assessment of joint effects of multiple SNPs, including interactions and linkage.
  • To efficiently explore multi-SNP model spaces and identify optimal models for genetic association studies.

Main Methods:

  • Proposed a Bayesian graphical model for multi-SNP association analysis.
  • Utilized the Mode Oriented Stochastic Search (MOSS) algorithm for efficient model space exploration.
  • Applied the methodology to the CGEM breast cancer GWAS dataset.

Main Results:

  • The MOSS algorithm successfully identified multi-locus models with high posterior probabilities.
  • Several biologically relevant SNPs were detected, including some missed by standard single-SNP analyses.
  • The approach demonstrated effectiveness in uncovering complex genetic associations in GWAS data.

Conclusions:

  • The developed Bayesian graphical model offers a powerful alternative to standard GWAS analysis for complex diseases.
  • The genMOSS R package provides an open-source implementation for broader application.
  • This methodology advances the ability to detect novel genetic associations and understand disease architecture.