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

Multiple Allele Traits01:49

Multiple Allele Traits

The Concept of Multiple Allelism
Multiple Allele Traits01:49

Multiple Allele Traits

The Concept of Multiple Allelism
Polygenic Traits01:18

Polygenic Traits

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...
Polygenic Traits01:18

Polygenic Traits

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...
Pleiotropy01:33

Pleiotropy

Pleiotropy is the phenomenon in which a single gene impacts multiple, seemingly unrelated phenotypic traits. For example, defects in the SOX10 gene cause Waardenburg Syndrome Type 4, or WS4, which can cause defects in pigmentation, hearing impairments, and an absence of intestinal contractions necessary for elimination. This diversity of phenotypes results from the expression pattern of SOX10 in early embryonic and fetal development. SOX10 is found in neural crest cells that form melanocytes,...
Behavioral Genetics and Its Designs01:23

Behavioral Genetics and Its Designs

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...

You might also read

Related Articles

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

Sort by
Same author

Genetics of major depressive disorder in a homogeneous population with uniform phenotyping.

Molecular psychiatry·2026
Same author

Causation Between Smoking Quantity and Depressive Symptoms in Young Adults: Evidence From Novel Cross-Lagged Twin Models.

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

The Power to Resolve Cultural Transmission and Sibling Interaction Using Polygenic Scores.

Behavior genetics·2025
Same author

Genetic and environmental contributions to variation in plasma phosphorylated tau 217.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2025
Same author

Measurement Error and Power in Family-Based Extensions to Mendelian Randomization.

Behavior genetics·2025
Same author

Intergenerational transmission of complex traits and the offspring methylome.

Molecular psychiatry·2025
Same journal

Twins With Feingold Syndrome: Overview and Interview/Twin Research Summaries: Pseudoamonoamniotic Twins; Selective Fetal Growth Restriction in Monoamniotic Twins; Twin Authorship Attribution; Twins Discordant for Clubfoot/Human Interest: Twins with Different Fathers; Biological Relatedness in a Married Couple; Birth of Identical Quadruplets; Twins Switching Places.

Twin research and human genetics : the official journal of the International Society for Twin Studies·2026
Same journal

Twin-Based Randomized Controlled Trials in Nutritional Research: A Scoping Review.

Twin research and human genetics : the official journal of the International Society for Twin Studies·2026
Same journal

The Population-Based Hungarian Twin Registry: Current Register Data, Researches and Linkages.

Twin research and human genetics : the official journal of the International Society for Twin Studies·2026
Same journal

Abstracts for the 20th Congress of the International Society of Twin Studies, Colombo, Sri Lanka, 10-12 August 2025.

Twin research and human genetics : the official journal of the International Society for Twin Studies·2026
Same journal

THG volume 28 issue 1 Cover.

Twin research and human genetics : the official journal of the International Society for Twin Studies·2026
Same journal

Twins and Look-Alikes: Perspectives on Human Reproductive Cloning/Twin Research Reviews: Infantile Pyknocytosis in a Dizygotic Twin; MZ Twin Discordance for Hemimicrencephaly; Unusual Dental Development, with Expert Commentary; Twin Study of 'Gaze Fingerprint Signatures'/Human Interest: Identical Twin Executives at Odds; Loss of Identical Twin, Jim Whittaker; Identical Twin Artists; Twin Wisdom Captured in Stone.

Twin research and human genetics : the official journal of the International Society for Twin Studies·2026
See all related articles

Related Experiment Video

Updated: Jun 6, 2026

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
06:52

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

Published on: September 17, 2019

Genetic association in multivariate phenotypic data: power in five models.

Camelia C Minica1, Dorret I Boomsma, Sophie van der Sluis

  • 1Department of Psychology, FMG, University of Amsterdam, The Netherlands.

Twin Research and Human Genetics : the Official Journal of the International Society for Twin Studies
|December 15, 2010
PubMed
Summary
This summary is machine-generated.

This study evaluated data analytic strategies for detecting a single genetic variant (GV) effect in twin data. Exploratory factor analysis (EFA) and sum score ANOVA were most powerful when the GV affected all phenotypes.

More Related Videos

Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease
08:51

Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease

Published on: September 20, 2024

Related Experiment Videos

Last Updated: Jun 6, 2026

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
06:52

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

Published on: September 17, 2019

Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease
08:51

Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease

Published on: September 20, 2024

Area of Science:

  • Quantitative genetics
  • Statistical genetics
  • Behavioral genetics

Background:

  • Detecting the influence of specific genetic variants (GVs) on complex traits is crucial in genetic research.
  • Multivariate data analysis offers powerful tools to disentangle genetic and environmental influences on multiple phenotypes.

Purpose of the Study:

  • To compare the statistical power of different data analytic strategies in detecting the effect of a single genetic variant (GV) within multivariate twin data.
  • To investigate how phenotypic correlations and the pattern of GV effects influence the power of these strategies.

Main Methods:

  • Simulated monozygotic and dizygotic twin phenotypic data based on common factor and simplex models.
  • Calculated statistical power for detecting GVs using Analysis of Variance (ANOVA) on sum scores, Multivariate ANOVA (MANOVA), and Exploratory Factor Analysis (EFA).
  • Assessed power under different scenarios, including GVs affecting all or a subset of phenotypes.

Main Results:

  • When a GV affects all phenotypes, sum score ANOVA and EFA demonstrate the highest power, whereas MANOVA's power decreases with higher phenotypic correlations.
  • When a GV affects only a subset of phenotypes, EFA and MANOVA are more powerful than sum score ANOVA, with increased correlations potentially boosting their power.
  • Modeling GV effects directly on phenotypes in EFA yields power comparable to MANOVA.

Conclusions:

  • The choice of data analytic strategy significantly impacts the power to detect genetic variant effects in twin studies.
  • EFA and sum score ANOVA are robust when genetic variants influence all measured phenotypes.
  • MANOVA and EFA are more suitable for detecting genetic variants that affect only a subset of phenotypes.