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

Pleiotropy01:33

Pleiotropy

31.0K
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,...
31.0K
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

12.1K
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...
12.1K
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

11.4K
Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
11.4K
Epistasis Analysis01:09

Epistasis Analysis

4.9K
Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
4.9K
Polygenic Traits01:18

Polygenic Traits

57.9K
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...
57.9K
Polygenic Traits01:18

Polygenic Traits

7.1K
7.1K

You might also read

Related Articles

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

Sort by
Same author

Social vulnerability and the mental health consequences of the death of a close friend in older adulthood.

The journals of gerontology. Series B, Psychological sciences and social sciences·2026
Same author

Protocol for first-hit oncogenic organoid modeling and lentiviral functional screening.

STAR protocols·2026
Same author

The Offender Personality Disorder Pathway for Men: Staff Perceptions About Possible Impact on Re-offending in High-Risk Individuals with Personality Disorder.

International journal of offender therapy and comparative criminology·2026
Same author

Epigenetic fingerprints link early-onset colon and rectal cancer to pesticide exposure.

Nature medicine·2026
Same author

Inactivation of CDKN2AARF Promotes p53-Independent Remodeling of the PDAC Tumor Microenvironment.

Cancer research·2026
Same author

<i>CanDrivR-CS</i>: a cancer-specific machine learning framework for distinguishing recurrent and rare variants.

Bioinformatics advances·2026
Same journal

Another 10 years of PLOS Computational Biology: A data-driven reflection on trends in genomics research.

PLoS computational biology·2026
Same journal

Mobility data resolution needed to inform predictive models of spatial epidemic spread from mobile phone data.

PLoS computational biology·2026
Same journal

DeepMethylation: A deep learning framework for tissue-specific DNA methylation prediction and functional variant annotation.

PLoS computational biology·2026
Same journal

Redefining and estimating the early-phase reproduction ratio for epidemic outbreaks in spatially structured populations.

PLoS computational biology·2026
Same journal

Optimized phenotype definitions boost GWAS power.

PLoS computational biology·2026
Same journal

Detection, communication, and individual identification with deep audio embeddings: A case study with North Atlantic right whales.

PLoS computational biology·2026
See all related articles

Related Experiment Video

Updated: Apr 21, 2026

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

4.6K

Canonical correlation analysis for gene-based pleiotropy discovery.

Jose A Seoane1, Colin Campbell2, Ian N M Day1

  • 1School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom.

Plos Computational Biology
|October 21, 2014
PubMed
Summary
This summary is machine-generated.

This study introduces a new method using Canonical Correlation Analysis (CCA) to find genetic associations with multiple traits. The approach enhances statistical power, identifying novel links between genes and complex diseases.

More Related Videos

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
07:11

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

Published on: November 10, 2023

3.1K
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

9.2K

Related Experiment Videos

Last Updated: Apr 21, 2026

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

4.6K
Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
07:11

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

Published on: November 10, 2023

3.1K
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

9.2K

Area of Science:

  • Genetics
  • Biostatistics
  • Complex Trait Analysis

Background:

  • Genome-wide association studies (GWAS) identify genetic variants for complex traits and diseases.
  • Testing variants for pleiotropy (multiple phenotypes) and gene-based associations (multiple variants) increases statistical power.
  • Canonical Correlation Analysis (CCA) can integrate these approaches by analyzing relationships between sets of variables.

Purpose of the Study:

  • To adapt Canonical Correlation Analysis (CCA) for genetic association studies.
  • To improve statistical power for detecting genetic associations with complex traits and diseases.
  • To identify novel pleiotropic and gene-based genetic associations.

Main Methods:

  • Utilized Canonical Correlation Analysis (CCA) with an attribute selection strategy based on a binary genetic algorithm.
  • Applied the method to a UK prospective cohort study (British Women's Heart and Health Study) of 4286 women.
  • Considered modules of genetic variation and sets of phenotypes to manage attribute numbers relative to samples.

Main Results:

  • Achieved improved statistical power in detecting previously reported genetic associations.
  • Identified novel pleiotropic associations between genetic variants and phenotypes.
  • Discovered gene-based associations (e.g., NSF with triglycerides) and associations of multiple genes (e.g., ACSM3, ERI2, IL18RAP, IL23RAP, NRG1) with left ventricular hypertrophy phenotypes.

Conclusions:

  • The adapted CCA method enhances power for genetic association studies.
  • Novel pleiotropic and gene-based associations were identified, including links to cardiovascular phenotypes.
  • This approach offers a powerful tool for dissecting the genetic architecture of complex traits and diseases.