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

Trait and State Self-Esteem02:08

Trait and State Self-Esteem

11.5K
The term self-esteem is often used generically, to refer to how people feel about themselves. However, according to research, there are three distinct constructs that should not be used interchangeably (Brown & Marshall, 2006). 
11.5K
Polygenic Traits01:18

Polygenic Traits

69.1K
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...
69.1K
Multiple Allele Traits01:49

Multiple Allele Traits

38.2K
The Concept of Multiple Allelism
38.2K
Traits and States01:17

Traits and States

563
Personality traits represent consistent patterns in behavior, thoughts, and emotions, reflecting an individual's tendencies across various situations. For example, extraversion, a well-known trait, manifests in individuals as talkative, energetic, and enthusiastic behaviors. These traits are stable over time, offering a reliable framework for predicting how people might act in different contexts. However, they do not define every moment of an individual's life. In contrast to traits,...
563
X-linked Traits01:19

X-linked Traits

58.8K
In most mammalian species, females have two X sex chromosomes and males have an X and Y. As a result, mutations on the X chromosome in females may be masked by the presence of a normal allele on the second X. In contrast, a mutation on the X chromosome in males more often causes observable biological defects, as there is no normal X to compensate. Trait variations arising from mutations on the X chromosome are called “X-linked”.
58.8K
Trait Centrality01:21

Trait Centrality

199
Trait centrality refers to the degree to which a particular characteristic influences the overall impression of an individual. Some traits exert a disproportionately strong impact on perception, shaping how people interpret other attributes of a person. Solomon Asch first systematically studied this phenomenon in 1946.Asch’s Experiment on Trait CentralityAsch's seminal study demonstrated the centrality of certain traits through a controlled experiment. Participants were presented with a...
199

You might also read

Related Articles

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

Sort by
Same author

Genetic and transcriptomic determinants of disseminated coccidioidomycosis identify a founder variant in <i>NLRX1</i> and ancestry-specific rare variants in immune response genes.

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

Quantitative trait loci mapping of gene expression and chromatin accessibility in primary fibroblasts reveals shared allelic effects between Latin American and European ancestries.

BMC genomics·2026
Same author

Challenges and recommendations in establishing national human diversity genomic projects.

Nature methods·2026
Same author

Leveraging tumor dynamics to discover mutations influencing progression and treatment response for precision oncology.

Genome medicine·2026
Same author

Genome-wide analysis implicates inner ear development in Ménière disease.

American journal of human genetics·2026
Same author

Embeddings of clinical codes enable knowledge-grounded AI in medicine.

NPJ digital medicine·2026

Related Experiment Video

Updated: Feb 8, 2026

A Unified Methodological Framework for Vestibular Schwannoma Research
08:43

A Unified Methodological Framework for Vestibular Schwannoma Research

Published on: June 20, 2017

7.8K

A unifying framework for joint trait analysis under a non-infinitesimal model.

Ruth Johnson1, Huwenbo Shi2, Bogdan Pasaniuc2,3,4

  • 1Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA.

Bioinformatics (Oxford, England)
|June 29, 2018
PubMed
Summary

Genome-wide association studies (GWAS) reveal shared risk regions across diseases. Our new framework, UNITY, quantifies genetic overlap between traits, offering insights into complex disease etiology.

More Related Videos

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

2.6K
Watershed Planning within a Quantitative Scenario Analysis Framework
12:44

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

8.7K

Related Experiment Videos

Last Updated: Feb 8, 2026

A Unified Methodological Framework for Vestibular Schwannoma Research
08:43

A Unified Methodological Framework for Vestibular Schwannoma Research

Published on: June 20, 2017

7.8K
Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

2.6K
Watershed Planning within a Quantitative Scenario Analysis Framework
12:44

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

8.7K

Area of Science:

  • Genetics
  • Bioinformatics
  • Statistical Genetics

Background:

  • Genome-wide association studies (GWAS) frequently identify overlapping genomic regions associated with diverse diseases and traits.
  • Understanding whether this overlap stems from shared causal variants or statistical chance is crucial for elucidating the etiology of complex conditions.

Purpose of the Study:

  • To introduce UNITY (Unifying Non-Infinitesimal Trait analYsis), a novel computational framework for quantifying genetic overlap between trait pairs.
  • To provide a flexible and unifying approach for analyzing shared genetic architecture underlying complex traits.

Main Methods:

  • Development of a Bayesian generative model that links trait overlap to GWAS summary statistics, accommodating non-infinitesimal genetic architectures.
  • Implementation of a Metropolis-Hastings sampler for estimating posterior densities of genetic overlap parameters.
  • Validation through extensive simulations and application to real-world GWAS data for height and body mass index.

Main Results:

  • The UNITY framework successfully quantifies genetic overlap between complex traits using GWAS summary statistics.
  • Analysis of height and body mass index GWAS data yielded results consistent with established genetic correlations.
  • The proposed Bayesian model and sampling method are effective for estimating genetic overlap.

Conclusions:

  • UNITY provides a robust method for dissecting shared genetic influences across complex traits and diseases.
  • This framework advances our understanding of pleiotropy and shared etiology in human complex traits.
  • The freely available UNITY software facilitates broader research into the genetic underpinnings of related phenotypes.