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

15.6K
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...
15.6K
Gene-Environment Interactions01:20

Gene-Environment Interactions

1.2K
Gene expression is a dynamic process that is significantly influenced by environmental factors. This interaction underlies the complex nature of biological development and the phenotypic differences observed among individuals, even among those with identical genetic makeups. Factors such as radiation, temperature, behavior, nutrition, and stress play pivotal roles in determining how genes are expressed. The concept of the reaction range is central to understanding this interaction. It posits...
1.2K
Genome Size and the Evolution of New Genes03:21

Genome Size and the Evolution of New Genes

9.1K
While every living organism has a genome of some kind (be it RNA, or DNA), there is considerable variation in the sizes of these blueprints. One major factor that impacts genome size is whether the organism is prokaryotic or eukaryotic. In prokaryotes, the genome contains little to no non-coding sequence, such that genes are tightly clustered in groups or operons sequentially along the chromosome. Conversely, the genes in eukaryotes are punctuated by long stretches of non-coding sequence.
9.1K
Genome Size and the Evolution of New Genes03:21

Genome Size and the Evolution of New Genes

3.4K
3.4K
Genomics02:02

Genomics

40.5K
Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
40.5K
Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes02:16

Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes

16.0K
The present-day mitochondrial and chloroplast genomes have retained some of the characteristics of their ancestral prokaryotes and also have acquired new attributes during their evolution within eukaryotic cells. Like prokaryotic genomes, mitochondrial and chloroplast genomes neither bind with histone-like proteins nor show complex packaging into chromosome-like structures, as observed in eukaryotes. Unlike mitotic cell divisions observed in eukaryotic cells, mitochondria and chloroplasts...
16.0K

You might also read

Related Articles

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

Sort by
Same author

An epigenetic clock for chronological age estimation in East Asian populations.

NAR genomics and bioinformatics·2026
Same author

Gut microbial resistance and metabolism of selective serotonin reuptake inhibitors drive multidrug resistance and contribute to antidepressant tachyphylaxis.

Drug metabolism and disposition: the biological fate of chemicals·2026
Same author

Prognostic Significance of <i>NOTCH3</i> Small Vessel Disease Staging for the <i>NOTCH3</i> p.R544C Variant.

Neurology. Genetics·2026
Same author

Multimodal machine learning for major depressive disorder: Integrating EEG functional connectivity and clinical variables to enhance diagnostic accuracy.

Psychiatry research·2026
Same author

Dysregulated miRNAs and downstream gene expression associated with poor treatment response in first-episode psychosis.

Brain, behavior, & immunity - health·2026
Same author

Using multi-trait polygenic scores to predict lithium responsiveness in patients with bipolar disorder.

medRxiv : the preprint server for health sciences·2026
Same journal

Potential role of the <i>Trpv4 c.1491+1G>A</i> mutation in pulmonary fibrosis in a gene-edited mouse model.

Frontiers in genetics·2026
Same journal

Utilization of whole exome sequencing to identify hereditary mutations in Palestinian families with hereditary cancers.

Frontiers in genetics·2026
Same journal

Research of N-acetyl-L-cysteine on CD40-CD40L pathway in pulmonary fibrosis induced by silicon dioxide.

Frontiers in genetics·2026
Same journal

Novel variants in LSS related hypotrichosis simplex 14.

Frontiers in genetics·2026
Same journal

Network-based analysis identifies shared mechanisms between ischemic stroke and myocardial infarction and therapeutic ingredients of Buyang Huanwu Decoction.

Frontiers in genetics·2026
Same journal

GWAS analysis of a depression cohort defined by an EHR-phenotyping algorithm reveals the role of immune regulations in depression risk.

Frontiers in genetics·2026
See all related articles

Related Experiment Video

Updated: Jan 30, 2026

Genome-wide Analysis using ChIP to Identify Isoform-specific Gene Targets
11:19

Genome-wide Analysis using ChIP to Identify Isoform-specific Gene Targets

Published on: July 7, 2010

15.0K

Genome-Wide Gene-Environment Interaction Analysis Using Set-Based Association Tests.

Wan-Yu Lin1,2, Ching-Chieh Huang1, Yu-Li Liu3

  • 1Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan.

Frontiers in Genetics
|January 30, 2019
PubMed
Summary
This summary is machine-generated.

The adaptive combination of Bayes factors method (ADABF) is a powerful tool for detecting gene-environment interactions (G × E) in complex diseases. It demonstrates strong performance and efficiency in genome-wide analyses, making it a recommended approach.

Keywords:
Taiwan Biobankdiastolic blood pressuregene-alcohol interactionhypertensionmultiple testing correctionsystolic blood pressure

More Related Videos

Genome-Wide CRISPR Screen for Unveiling Radiosensitive and Radioresistant Genes
08:32

Genome-Wide CRISPR Screen for Unveiling Radiosensitive and Radioresistant Genes

Published on: May 23, 2025

1.2K
Genome-wide Gene Deletions in Streptococcus sanguinis by High Throughput PCR
14:07

Genome-wide Gene Deletions in Streptococcus sanguinis by High Throughput PCR

Published on: November 23, 2012

17.0K

Related Experiment Videos

Last Updated: Jan 30, 2026

Genome-wide Analysis using ChIP to Identify Isoform-specific Gene Targets
11:19

Genome-wide Analysis using ChIP to Identify Isoform-specific Gene Targets

Published on: July 7, 2010

15.0K
Genome-Wide CRISPR Screen for Unveiling Radiosensitive and Radioresistant Genes
08:32

Genome-Wide CRISPR Screen for Unveiling Radiosensitive and Radioresistant Genes

Published on: May 23, 2025

1.2K
Genome-wide Gene Deletions in Streptococcus sanguinis by High Throughput PCR
14:07

Genome-wide Gene Deletions in Streptococcus sanguinis by High Throughput PCR

Published on: November 23, 2012

17.0K

Area of Science:

  • Genetics
  • Biostatistics
  • Epidemiology

Background:

  • Identifying gene-environment interactions (G × E) is crucial for understanding complex diseases and guiding personalized medicine.
  • Existing methods for detecting G × E require enhancement for greater power and accuracy in genome-wide studies.

Purpose of the Study:

  • To evaluate the performance of the adaptive combination of Bayes factors method (ADABF) as a gene-based G × E test.
  • To compare ADABF with other established G × E detection methods using simulations and real-world data.

Main Methods:

  • Simulations were conducted to assess the power and robustness of ADABF and six other G × E tests, including SBERIA and GESAT.
  • The Taiwan Biobank dataset was utilized to explore gene × alcohol interactions affecting blood pressure levels.

Main Results:

  • ADABF and SBERIA exhibited superior power compared to other G × E tests in simulations.
  • SBERIA showed a power loss under specific effect direction scenarios.
  • The ADAMTS7P1 gene was identified as interacting with alcohol consumption on diastolic blood pressure in the Taiwan Biobank data.

Conclusions:

  • ADABF is a powerful and robust method for genome-wide G × E analysis, offering a good balance of validity, power, and computational efficiency.
  • ADABF is recommended for future genome-wide G × E studies due to its comprehensive performance characteristics.