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

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

16.9K
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...
16.9K
Polygenic Traits01:18

Polygenic Traits

70.8K
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...
70.8K
Polygenic Traits01:18

Polygenic Traits

11.5K
11.5K
Principles of Pharmacogenetics: Types of Genetic Variants01:27

Principles of Pharmacogenetics: Types of Genetic Variants

114
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...
114
Pharmacogenetics and Pharmacogenomics: Overview01:29

Pharmacogenetics and Pharmacogenomics: Overview

186
Pharmacogenetics and pharmacogenomics examine how genetic factors influence an individual's response to drugs. While pharmacogenetics focuses on the impact of specific genetic variants on drug effects, pharmacogenomics takes a broader approach, studying how genetic variation across populations contributes to differences in drug responses. These fields aim to explain why individuals may experience varying levels of efficacy or adverse reactions to the same medication.Variability in drug...
186
Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

94
Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
94

You might also read

Related Articles

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

Sort by
Same author

Letter to the Editor: Comment on Zhang H, et al. The Effects of Inactive Platelet-Rich Plasma at Different Injection Time on Prefabricated Flap Viability in Rabbits (Ann Plast Surg. 2021;86:701-706).

Annals of plastic surgery·2022
Same author

The application of 3D bioprinting in urological diseases.

Materials today. Bio·2022
Same author

Liquid Foam Stabilized by a CO<sub>2</sub>-Responsive Surfactant and Similarly Charged Cellulose Nanofibers for Reversibly Plugging in Porous Media.

ACS applied materials & interfaces·2022
Same author

Fatigue-free artificial ionic skin toughened by self-healable elastic nanomesh.

Nature communications·2022
Same author

Analytical Model for Early Design Stage of Cable-Stayed Suspension Bridges Based on Hellinger-Reissner Variational Method.

Materials (Basel, Switzerland)·2022
Same author

SMAD4, activated by the TCR-triggered MEK/ERK signaling pathway, critically regulates CD8<sup>+</sup> T cell cytotoxic function.

Science advances·2022

Related Experiment Video

Updated: Apr 15, 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

5.0K

Testing for polygenic effects in genome-wide association studies.

Wei Pan1, Yue-Ming Chen, Peng Wei

  • 1Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota.

Genetic Epidemiology
|April 8, 2015
PubMed
Summary

We developed new adaptive polygenic tests that significantly improve statistical power for genome-wide association studies (GWAS). These methods enhance the polygenic risk score (PRS) test by using the whole sample, offering a more efficient approach for genetic research.

Keywords:
GWASSPU testsSSU testSSUw testaSPU testlogistic regressionpolygenic variationsum test

More Related Videos

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

10.9K
Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
11:35

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Published on: August 21, 2016

13.7K

Related Experiment Videos

Last Updated: Apr 15, 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

5.0K
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

10.9K
Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
11:35

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Published on: August 21, 2016

13.7K

Area of Science:

  • Genetics
  • Statistical Genetics
  • Bioinformatics

Background:

  • The polygenic risk score (PRS) test was proposed to confirm associations with numerous single nucleotide polymorphisms (SNPs) of small effect sizes, supporting polygenic theories in complex diseases.
  • The PRS test employs a data-splitting strategy, using one part of the sample to select SNPs and the other to test their aggregated effects.

Purpose of the Study:

  • To evaluate and enhance the performance of the PRS test for genome-wide association studies (GWAS) data.
  • To develop novel polygenic testing methods that overcome the limitations of the PRS test's data-splitting strategy.

Main Methods:

  • Analyzed the PRS test, identifying its connection to the Sum test and motivating the development of alternative polygenic tests.
  • Reformulated the PRS test to create adaptive tests, closely related to the adaptive sum of powered score (SPU) test, by avoiding data splitting.

Main Results:

  • The analysis revealed connections between the PRS test and the Sum test, suggesting potential for more powerful polygenic tests.
  • Adaptive tests, particularly the whole sample-based adaptive SPU test, demonstrated dramatically improved statistical power compared to the PRS test using both simulated and real GWAS data.

Conclusions:

  • The study highlights the limitations of the PRS test's data-splitting approach and its statistical inefficiency.
  • The whole sample-based adaptive SPU test is recommended for polygenic testing due to its superior performance, simplicity, and enhanced statistical power in GWAS.