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

37.7K
The Concept of Multiple Allelism
37.7K
Multiple Comparison Tests01:13

Multiple Comparison Tests

4.3K
Multiple comparison test, abbreviated as MCT, is a post hoc analysis generally performed after comparing multiple samples with one or more tests. An MCT will help identify a significantly different sample among multiple samples or a factor among multiple factors.
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
4.3K
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

18.5K
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%...
18.5K
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

15.1K
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...
15.1K

You might also read

Related Articles

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

Sort by
Same author

GEiPRS: a fast and powerful machine learning method for polygenic risk score prediction by leveraging genotype-environment interactions.

Briefings in bioinformatics·2026
Same author

A Tumor-Promoting Inflammatory SPP1+ Macrophage-IL6-CRP Axis Drives Immune Dysfunction in Bladder Cancer.

Cancer discovery·2026
Same author

Plain language summary of publication: Comparing nivolumab and neoadjuvant chemotherapy with placebo and neoadjuvant chemotherapy in participants with newly diagnosed estrogen receptor-positive breast cancer in the CheckMate 7FL clinical trial.

Future oncology (London, England)·2025
Same author

Assessing Benefit in Patients With Heart Failure and Reduced Ejection Fraction: Analysis of the VICTORIA Trial Using Novel Prognostic Risk Stratification.

Journal of cardiac failure·2025
Same author

Circulating Tumor DNA Genotyping of Intrinsic and Acquired Gene Alterations in Patients With Advanced Breast Cancer Receiving Palbociclib: Biomarker Results From POLARIS Study.

JCO precision oncology·2025
Same author

Study duration prediction for clinical trials with time-to-event endpoints accounting for heterogeneous population.

Journal of biopharmaceutical statistics·2025

Related Experiment Video

Updated: Dec 19, 2025

Multi-locus Variable-number Tandem-repeat Analysis of the Fish-pathogenic Bacterium Yersinia ruckeri by Multiplex PCR and Capillary Electrophoresis
10:33

Multi-locus Variable-number Tandem-repeat Analysis of the Fish-pathogenic Bacterium Yersinia ruckeri by Multiplex PCR and Capillary Electrophoresis

Published on: June 17, 2019

11.2K

Multi-trait analysis of rare-variant association summary statistics using MTAR.

Lan Luo1, Judong Shen2, Hong Zhang2

  • 1Department of Statistics, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA.

Nature Communications
|June 7, 2020
PubMed
Summary

We developed a new method, multi-trait analysis of rare-variant associations (MTAR), to discover more genes linked to multiple traits. MTAR significantly increases gene discovery power for complex diseases by analyzing rare variants across traits.

More Related Videos

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
09:37

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information

Published on: August 15, 2019

10.2K
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

4.7K

Related Experiment Videos

Last Updated: Dec 19, 2025

Multi-locus Variable-number Tandem-repeat Analysis of the Fish-pathogenic Bacterium Yersinia ruckeri by Multiplex PCR and Capillary Electrophoresis
10:33

Multi-locus Variable-number Tandem-repeat Analysis of the Fish-pathogenic Bacterium Yersinia ruckeri by Multiplex PCR and Capillary Electrophoresis

Published on: June 17, 2019

11.2K
Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
09:37

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information

Published on: August 15, 2019

10.2K
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

4.7K

Area of Science:

  • Genetics
  • Statistical Genetics
  • Bioinformatics

Background:

  • Integrating evidence across multiple traits enhances gene discovery and reveals pleiotropy.
  • Current multi-trait methods often focus on common variants in genome-wide association studies (GWAS).

Purpose of the Study:

  • Introduce a novel framework, multi-trait analysis of rare-variant associations (MTAR), for joint analysis of rare variants and multiple traits.
  • Improve power for gene discovery by leveraging genome-wide genetic correlation to assess gene-level effect heterogeneity across traits.

Main Methods:

  • Developed the MTAR framework for analyzing association summary statistics of multiple rare variants across different traits.
  • Applied MTAR to rare-variant summary statistics for three lipid traits using data from the Global Lipids Genetics Consortium.

Main Results:

  • MTAR identified 139 genome-wide significant genes, an increase from 99 identified by single-trait tests.
  • Discovered 11 novel lipid-associated genes, with 7 successfully replicated in an independent UK Biobank GWAS analysis.

Conclusions:

  • MTAR demonstrates substantially greater power for gene discovery compared to single-trait-based tests.
  • Highlights the utility of MTAR for identifying novel genes associated with complex traits and understanding pleiotropy.