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

Case Studies01:22

Case Studies

13.9K
There are many research methods available to psychologists in their efforts to understand, describe, and explain behavior and the cognitive and biological processes that underlie it.
13.9K
Principles of Pharmacogenetics: Types of Genetic Variants01:27

Principles of Pharmacogenetics: Types of Genetic Variants

98
The human genome is over 99.9% identical between individuals, yet genetic differences exist at millions of bases. The human genome contains approximately 3 million variant positions per individual, many of which are heterozygous, contributing to genetic diversity and individual traits. Genetic variations include single-nucleotide polymorphisms (SNPs), insertions, deletions, and copy number variations (CNVs).SNPs, the most common variation, involve single-base changes in DNA. These can be...
98
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

16.7K
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...
16.7K
Multiple Allele Traits01:49

Multiple Allele Traits

38.8K
The Concept of Multiple Allelism
38.8K
Multiple Allele Traits01:49

Multiple Allele Traits

15.0K
15.0K
Genetic Lingo01:11

Genetic Lingo

118.1K
Overview
118.1K

You might also read

Related Articles

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

Sort by
Same author

The Biobank Rare Variant consortium powers the discovery of rare genetic associations through global collaboration.

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

Mechanism of age-related accumulation of mtDNA mutations in human blood.

Nature·2026
Same author

Systematic common and rare variant association testing in 392,030 whole genomes in <i>All of Us</i>.

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

Effect of ancestry and shared genetic architecture of serious mental illness on symptoms and cognition in an admixed Latin American population.

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

Meta-analysis across six global biobanks identifies recessive coding associations with complex traits and diseases.

American journal of human genetics·2026
Same author

Phenome-derived polygenic scores and social determinants jointly shape context-dependent disease risk.

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

Characterisation of the SMN1/2 locus using a highly specific variant caller on whole-genome sequence data from 500,000 individuals.

European journal of human genetics : EJHG·2026
Same journal

When truncation is not loss of function: neo-tail architecture as a determinant of pathogenicity in NMD-escaping frameshift variants.

European journal of human genetics : EJHG·2026
Same journal

CMIP as a novel candidate gene for neurodevelopmental and neuropsychiatric disorders.

European journal of human genetics : EJHG·2026
Same journal

Parent and professional experiences of a clinical trial of prenatal and postnatal stem cell therapy for severe osteogenesis imperfecta.

European journal of human genetics : EJHG·2026
Same journal

Scoping review and recommendations for development and delivery of education resources for reproductive genetic carrier screening.

European journal of human genetics : EJHG·2026
Same journal

Australian parents' perspectives on extended genomic screening: what information to return and when?

European journal of human genetics : EJHG·2026
See all related articles

Related Experiment Video

Updated: Apr 4, 2026

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila
06:41

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila

Published on: August 20, 2019

14.5K

Phenotypic extremes in rare variant study designs.

Gina M Peloso1,2,3, Daniel J Rader4, Stacey Gabriel2

  • 1Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA, USA.

European Journal of Human Genetics : EJHG
|September 10, 2015
PubMed
Summary
This summary is machine-generated.

Studying extreme phenotypes significantly enhances the power to detect rare genetic variants associated with diseases like low high-density lipoprotein cholesterol (HDL-C). This approach is crucial for rare variant discovery in genetic research.

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

10.6K
Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
07:15

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

Published on: January 16, 2019

11.5K

Related Experiment Videos

Last Updated: Apr 4, 2026

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila
06:41

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila

Published on: August 20, 2019

14.5K
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

10.6K
Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
07:15

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

Published on: January 16, 2019

11.5K

Area of Science:

  • Genetics
  • Biostatistics
  • Population Health

Background:

  • Next-generation sequencing aims to find rare genetic variations linked to disease.
  • Detecting low-frequency variants is challenging due to decreased statistical power.
  • Existing methods for analyzing rare variants face interpretation hurdles.

Purpose of the Study:

  • To compare the effectiveness of extreme phenotypic sampling versus random sampling for identifying rare variants.
  • To investigate the impact of phenotypic selection on the power of genetic association studies.
  • To evaluate optimal meta-analysis weighting strategies for combined study designs.

Main Methods:

  • Sequencing data analysis of the ABCA1 gene, known for its association with high-density lipoprotein cholesterol (HDL-C).
  • Empirical comparison of association strengths between a phenotypic extreme sample and a population-based random sample.
  • Simulation studies to assess the influence of extreme phenotypic selection on statistical power.

Main Results:

  • Phenotypic extreme sampling showed a stronger association with HDL-C (P=0.0006) compared to random sampling (P=0.03).
  • Extreme selection designs offer substantially greater power gains for rare variant studies than for common variants.
  • Meta-analysis combining extreme and random samples yielded lower power with traditional sample size weighting versus noncentrality parameter weighting.

Conclusions:

  • Extreme phenotypic sampling is critical for boosting power in rare variant association studies.
  • This design increases power by enhancing extreme sampling effects and identifying more relevant functional variants.
  • Noncentrality parameter weighting is superior to sample size weighting when meta-analyzing extreme and random samples.