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

32.4K
The Concept of Multiple Allelism
32.4K
Behavioral Genetics and Its Designs01:23

Behavioral Genetics and Its Designs

1.4K
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...
1.4K
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

1.5K
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
1.5K
Polygenic Traits01:18

Polygenic Traits

7.1K
7.1K
Polygenic Traits01:18

Polygenic Traits

58.2K
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...
58.2K
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

You might also read

Related Articles

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

Sort by
Same author

First Search for B→X_{s}νν[over ¯] Decays.

Physical review letters·2026
Same author

Correction to: Hepatitis C virus core protein epigenetically silences SFRP1 and enhances HCC aggressiveness by inducing epithelial-mesenchymal transition.

Oncogene·2026
Same author

Biphasic tentacle strike kinematics in predatory cuttlefish.

The Journal of experimental biology·2026
Same author

[Comparative study of clinical characteristics and prognosis between early- and late-onset rectal cancer].

Zhonghua wei chang wai ke za zhi = Chinese journal of gastrointestinal surgery·2025
Same author

Primary diffuse leptomeningeal atypical teratoid/rhabdoid tumours (ATRT) of childhood: a molecularly characterised case report and literature review.

Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery·2025
Same author

Hypoxaemia during one lung ventilation.

BJA education·2023
Same journal

Landscape genetics of the copal tree, Bursera cuneata (Burseraceae): the key role of the tropical dry forest in shaping connectivity at the regional scale.

Heredity·2026
Same journal

From Paleogene to Anthropocene: phylogeography, geographic patterns of traits, and chronology of evolutionary drivers in northeast Asian anurans.

Heredity·2026
Same journal

It is hard to be small: Inbreeding depression on male breeding success depends on body size in a threatened songbird.

Heredity·2026
Same journal

How precise are mutation rate estimates? Comparison of different approaches to estimate de novo mutation rates.

Heredity·2026
Same journal

Insights from farming Macrocystis pyrifera offshore: phenotypic analysis, genome-wide association studies, genomic selection.

Heredity·2026
Same journal

Genomic prediction of wild-derived powdery mildew resistance for strawberry (Fragaria × ananassa) pre-breeding.

Heredity·2026
See all related articles

Related Experiment Video

Updated: Apr 24, 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

Empirical Bayesian elastic net for multiple quantitative trait locus mapping.

A Huang1, S Xu2, X Cai1

  • 1Department of Electrical and Computer Engineering, University of Miami, Coral Gables, FL, USA.

Heredity
|September 11, 2014
PubMed
Summary
This summary is machine-generated.

A new algorithm, empirical Bayesian EN (EBEN), improves quantitative trait locus (QTL) mapping by better detecting linked QTLs. EBEN offers higher detection power with similar false discovery rates compared to existing methods.

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

9.2K
Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
14:06

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Published on: November 12, 2012

46.1K

Related Experiment Videos

Last Updated: Apr 24, 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
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
Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
14:06

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Published on: November 12, 2012

46.1K

Area of Science:

  • Genetics
  • Statistical Genomics
  • Bioinformatics

Background:

  • Multiple quantitative trait locus (QTL) mapping often involves high-dimensional sparse regression models to identify multiple linked QTLs.
  • High-density marker maps, enabled by sequencing advancements, frequently result in highly correlated genetic markers within QTL models.
  • Existing methods like Lasso, empirical Bayesian Lasso (EBlasso), and elastic net (EN) have limitations in detecting correlated QTLs.

Purpose of the Study:

  • To develop a novel and more powerful algorithm for multiple QTL mapping, specifically designed to address challenges posed by correlated genetic markers.
  • To enhance the detection power for linked QTLs in high-dimensional genetic data.

Main Methods:

  • Development of a novel empirical Bayesian EN (EBEN) algorithm, building upon the efficiency of the EBlasso algorithm.
  • Utilized simulation studies to compare the performance of EBEN against existing methods such as EN and EBlasso.
  • Applied the EBEN algorithm to analyze a real genetic dataset.

Main Results:

  • Simulation results showed that EBEN achieved higher power in QTL detection compared to EN and EBlasso, with a comparable false discovery rate.
  • EBEN demonstrated a superior ability to identify correlated QTLs that were missed by EN and EBlasso.
  • Analysis of a real dataset confirmed that EBEN detected more significant genetic effects than the other tested algorithms.

Conclusions:

  • The empirical Bayesian EN (EBEN) algorithm is a powerful tool for multiple QTL mapping, particularly effective in the presence of correlated genetic markers.
  • EBEN offers improved detection capabilities for linked QTLs, advancing the field of statistical genomics.
  • An R software package 'EBEN' is available, facilitating the application of this method in genetic research and other high-dimensional modeling scenarios.