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

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...
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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...

You might also read

Related Articles

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

Sort by
Same author

Calculating the Probability that a Previously Susceptible Individual is Infected as a Function of Time Following Exposure to SARS-CoV-2.

Infectious diseases and therapy·2026
Same author

Molecular features unique to circulating tumor DNA enable the tumor-naïve liquid biopsy of glioblastoma.

NPJ precision oncology·2026
Same author

Evaluation of Long-Read Genome Sequencing for Genomic Profiling of Myeloid Cancers.

The Journal of molecular diagnostics : JMD·2025
Same author

When two plus four does not equal six: Combining computational and functional evidence to classify BRCA1 key domain missense substitutions.

American journal of human genetics·2025
Same author

Conserved noncoding cis elements associated with hibernation modulate metabolic and behavioral adaptations in mice.

Science (New York, N.Y.)·2025
Same author

When Two plus Four Does Not Equal Six: Combining Computational and Functional Evidence to Classify BRCA1 Key Domain Missense Substitutions.

medRxiv : the preprint server for health sciences·2025
Same journal

Abstracts from Specialized Centers of Research Excellence (SCORE) on Sex Differences 2025 annual meeting.

BMC proceedings·2026
Same journal

Conference abstracts the 1st UDOM scientific conference on health: healthy lives and well-being for all: opportunities and challenges.

BMC proceedings·2026
Same journal

Entrepreneurship beyond the lab: commercializing your creative outputs.

BMC proceedings·2026
Same journal

The need to strengthen laboratory leadership, systems, and networks to enhance outbreak detection and resilience in Africa: proceedings of a regional workshop.

BMC proceedings·2026
Same journal

Abstracts from the Globesync Community Research and Sustainability 2025 (GlobeCoReS 2025).

BMC proceedings·2026
Same journal

Bauru International Craniofacial Symposium: Comprehensive Care, Policy and Advocacy Proceedings.

BMC proceedings·2026
See all related articles

Related Experiment Video

Updated: May 24, 2026

Genetic Profiling and Genome-Scale Dropout Screening to Identify Therapeutic Targets in Mouse Models of Malignant Peripheral Nerve Sheath Tumor
09:33

Genetic Profiling and Genome-Scale Dropout Screening to Identify Therapeutic Targets in Mouse Models of Malignant Peripheral Nerve Sheath Tumor

Published on: August 25, 2023

Case-control association testing by graphical modeling for the Genetic Analysis Workshop 17 mini-exome sequence data.

Haley J Abel1, Alun Thomas

  • 1Division of Genetic Epidemiology, University of Utah, 391 Chipeta Way, Salt Lake City, UT 84105, USA. alun@genepi.med.utah.edu.

BMC Proceedings
|March 1, 2012
PubMed
Summary
This summary is machine-generated.

This study uses graphical models to analyze genetic data, identifying relationships between disease traits, quantitative variables, and genetic loci. The approach effectively detects disease-associated loci with a low false-positive rate.

More Related Videos

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

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
10:17

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

Published on: November 3, 2010

Related Experiment Videos

Last Updated: May 24, 2026

Genetic Profiling and Genome-Scale Dropout Screening to Identify Therapeutic Targets in Mouse Models of Malignant Peripheral Nerve Sheath Tumor
09:33

Genetic Profiling and Genome-Scale Dropout Screening to Identify Therapeutic Targets in Mouse Models of Malignant Peripheral Nerve Sheath Tumor

Published on: August 25, 2023

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

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
10:17

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

Published on: November 3, 2010

Area of Science:

  • Genetics
  • Statistical genetics
  • Bioinformatics

Background:

  • Graphical models are increasingly used to analyze complex genetic data.
  • Understanding linkage disequilibrium is crucial for identifying genetic associations.
  • Previous methods require efficient generalization for large datasets.

Purpose of the Study:

  • To generalize graphical models for linkage disequilibrium analysis.
  • To estimate the conditional independence structure among variables in a genetic dataset.
  • To model relationships between disease traits, quantitative variables, covariates, and associated genetic loci.

Main Methods:

  • Utilized a stepwise approach for computational efficiency.
  • Extended previously described graphical model methods.
  • Applied the methods to the Genetic Analysis Workshop 17 unrelated individuals dataset (first 50 replicates).

Main Results:

  • Successfully estimated a model describing relationships between disease, quantitative variables, covariates, and associated loci.
  • Demonstrated the ability to describe relationships between outcomes and covariates.
  • Correctly detected associations between disease and several genetic loci.
  • Achieved a reasonable false-positive detection rate.

Conclusions:

  • The generalized graphical model approach is effective for analyzing complex genetic data.
  • The method can identify significant genetic loci associated with disease traits.
  • This approach offers a robust framework for exploring gene-environment and gene-gene interactions.