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

Behrens–Fisher Test00:57

Behrens–Fisher Test

278
The Behrens-Fisher test is a statistical method designed to address the Behrens-Fisher problem, which arises when comparing the means of two normally distributed populations with unequal variances. Unlike the Student's t-test, which assumes equal variances, the Behrens-Fisher test allows for mean comparison without this restrictive assumption. This flexibility makes it particularly valuable in scenarios where two independent samples exhibit normality but lack variance homogeneity.
This test...
278
Fisher's Exact Test01:08

Fisher's Exact Test

1.2K
Fisher's exact test is a statistical significance test widely used to analyze 2x2 contingency tables, particularly in situations where sample sizes are small. Unlike the chi-squared test, which approximates P-values and assumes minimum expected frequencies of at least five in each cell, Fisher's exact test calculates the exact probability (P-value) of observing the data or more extreme results under the null hypothesis. This feature makes it especially valuable when the assumptions of...
1.2K
Diffusion01:12

Diffusion

220.2K
Diffusion is the passive movement of substances down their concentration gradients—requiring no expenditure of cellular energy. Substances, such as molecules or ions, diffuse from an area of high concentration to an area of low concentration in the cytosol or across membranes. Eventually, the concentration will even out, with the substance moving randomly but causing no net change in concentration. Such a state is called dynamic equilibrium, which is essential for maintaining overall...
220.2K
Diffusion01:21

Diffusion

6.4K
Diffusion is a type of passive transport. In passive transport, a substance tends to move from an area of high concentration to an area of low concentration until the concentration is equal across the space. For example, take the diffusion of substances through the air. When someone opens a perfume bottle in a room filled with people, the perfume is at its highest concentration in the bottle and is at its lowest at the edges of the room. The perfume vapor will diffuse, or spread away, from the...
6.4K
Theories of Dissolution: Diffusion Layer Model01:15

Theories of Dissolution: Diffusion Layer Model

1.8K
Dissolution, the process by which drug particles dissolve in a solvent, is explained by the diffusion layer model, a theoretical framework that simulates the absorption of oral drugs and allows us to analyze experimental data.
This process starts with a thin layer, saturated with the drug, forming at the interface between the solid and liquid. The solute then diffuses from this layer into the main solution. The Noyes-Whitney equation suggests that the rate of dissolution relies on the diffusion...
1.8K
Theory of Attribution I: Correspondent Inference Theory01:15

Theory of Attribution I: Correspondent Inference Theory

591
Correspondent inference theory, proposed by Jones and Davis in 1965, seeks to explain how individuals infer stable personality traits from observed behaviors. It suggests that people attribute actions to underlying dispositions rather than external circumstances, particularly when the behavior appears intentional and socially significant.Voluntary Behavior and Dispositional AttributionAccording to this theory, individuals are more likely to attribute behavior to personal traits when it appears...
591

You might also read

Related Articles

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

Sort by
Same author

Inference of Phylogenetic Networks From Sequence Data Using Composite Likelihood.

Systematic biology·2024
Same author

Bayesian function registration with random truncation.

PloS one·2023
Same author

Excursions in the Bayesian treatment of model error.

PloS one·2023
Same author

On the effects of selection and mutation on species tree inference.

Molecular phylogenetics and evolution·2022
Same author

Cryptic and abundant marine viruses at the evolutionary origins of Earth's RNA virome.

Science (New York, N.Y.)·2022
Same author

Comparative Performance of Popular Methods for Hybrid Detection using Genomic Data.

Systematic biology·2021

Related Experiment Video

Updated: Feb 9, 2026

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
12:39

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

11.7K

Bayesian inference of selection in the Wright-Fisher diffusion model.

Jeffrey J Gory1, Radu Herbei1, Laura S Kubatko2

  • 1Department of Statistics, The Ohio State University, Columbus, OH 43210, USA.

Statistical Applications in Genetics and Molecular Biology
|June 7, 2018
PubMed
Summary

This study introduces a new Bayesian method to estimate selection strength using population genetics data. The approach efficiently analyzes allele frequencies, offering a powerful tool for evolutionary biology research.

Keywords:
Wright-Fisher modeldiffusion modelselection

More Related Videos

Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3
11:10

Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3

Published on: December 27, 2010

12.8K
The Production of C. elegans Transgenes via Recombineering with the galK Selectable Marker
12:03

The Production of C. elegans Transgenes via Recombineering with the galK Selectable Marker

Published on: January 11, 2011

15.1K

Related Experiment Videos

Last Updated: Feb 9, 2026

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
12:39

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

11.7K
Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3
11:10

Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3

Published on: December 27, 2010

12.8K
The Production of C. elegans Transgenes via Recombineering with the galK Selectable Marker
12:03

The Production of C. elegans Transgenes via Recombineering with the galK Selectable Marker

Published on: January 11, 2011

15.1K

Area of Science:

  • Population Genetics
  • Evolutionary Biology
  • Statistical Genetics

Background:

  • Population-level allele frequency data is increasingly available.
  • Estimating population genetics parameters like selection strength is crucial.
  • Existing likelihood-based methods for Wright-Fisher diffusion are computationally intensive.

Purpose of the Study:

  • To develop an efficient Bayesian method for estimating selection strength.
  • To utilize exact sampling algorithms for improved computational efficiency.
  • To apply the method to both simulated and empirical population genetics data.

Main Methods:

  • Developed a Bayesian method based on the Wright-Fisher diffusion model.
  • Employed exact sampling algorithms to create a Markov chain Monte Carlo procedure.
  • Estimated the joint posterior distribution of selection coefficients and allele frequencies.

Main Results:

  • The Bayesian method performs well on simulated data when initial allele frequency assumptions are accurate.
  • Empirical data analysis on hypoxia in flies revealed strong positive selection on chromosome 2L.
  • Demonstrated the method's effectiveness for single-time point data.

Conclusions:

  • The developed Bayesian method offers an efficient alternative to existing computational approaches.
  • The findings support strong positive selection in a specific region of the fly genome.
  • Bayesian approaches provide advantages for population genetics inference in complex settings.