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

Probability Laws01:49

Probability Laws

Overview
Probability Histograms01:17

Probability Histograms

A probability histogram is a visual representation of a probability distribution. Similar a typical histogram, the probability histogram consists of contiguous (adjoining) boxes. It has both a horizontal axis and a vertical axis. The horizontal axis is labeled with what the data represents. The vertical axis is labeled with probability. Each rectangular bar in the histogram is 1 unit wide, which suggests that the area under each bar equals the probability, P(x), where x is 1, 2, 3, and so on.
Binomial Probability Distribution01:15

Binomial Probability Distribution

A binomial distribution is a probability distribution for a procedure with a fixed number of trials, where each trial can have only two outcomes.
The outcomes of a binomial experiment fit a binomial probability distribution. A statistical experiment can be classified as a binomial experiment if the following conditions are met:
There are a fixed number of trials. Think of trials as repetitions of an experiment. The letter n denotes the number of trials.
There are only two possible outcomes,...
Hardy-Weinberg Principle01:49

Hardy-Weinberg Principle

Diploid organisms have two alleles of each gene, one from each parent, in their somatic cells. Therefore, each individual contributes two alleles to the gene pool of the population. The gene pool of a population is the sum of every allele of all genes within that population and has some degree of variation. Genetic variation is typically expressed as a relative frequency, which is the percentage of the total population that has a given allele, genotype or phenotype.In the early 20th century,...
Distributions to Estimate Population Parameter01:26

Distributions to Estimate Population Parameter

The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...
Probability in Statistics01:14

Probability in Statistics

Probability is the likelihood of an event occurring. The term event is defined as a collection of results of a procedure. An event is a simple event when an outcome cannot be divided into simpler parts.
An example of a simple event is a coin toss. The result of a coin toss is either a head or a tail. Here, head and tail are two simple events. These two simple events make up the sample space. Further, the probability of an event occurring falls within the range of 0 to 1. The probability of an...

You might also read

Related Articles

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

Sort by
Same author

Corrigendum to "Exact calculation of the expected SFS in structured populations" [Theoretical Population Biology Volume 163(2025) 50-61].

Theoretical population biology·2026
Same author

Spider mite genotypes with higher growth rate suffer more from competition but exert stronger reproductive interference.

The Journal of animal ecology·2026
Same author

Combining Population Genomics With Ancient DNA to Understand Island Colonisation History of the Madagascar Turtle Dove.

Molecular ecology·2026
Same author

Molecular Responses to Climate Change: How Warming and Acidification Reshape the Proteome and Phosphoproteome of the Endangered Mira Chub.

Ecology and evolution·2026
Same author

Extending the IICR to complex nonstationary structured models.

Genetics·2026
Same author

Estimating the Effective Population Size Across Space and Time in the Critically Endangered Western Chimpanzee in Guinea-Bissau: Challenges and Implications for Conservation Management.

Evolutionary applications·2025
Same journal

Coexistence of piRNA and KZFP defense systems: Evolutionary dynamics of layered defense against transposable elements.

Genetics·2026
Same journal

Creation and manipulation of bipartite expression transgenes in C. elegans using phiC31 recombinase.

Genetics·2026
Same journal

Inherited long telomeres induce a genome-wide transcriptional response in budding yeast.

Genetics·2026
Same journal

Adaptive Dynamics of Quantitative Traits in a Steadily Changing Environment.

Genetics·2026
Same journal

Functional Landscape of Zebrafish Gonadotropins and Receptors: A Comprehensive Genetic Analysis.

Genetics·2026
Same journal

Synergistic actions of Nup43 and Myosin VI drive actin cone assembly during Drosophila spermiogenesis.

Genetics·2026
See all related articles

Related Experiment Video

Updated: Jun 25, 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

Approximate bayesian computation without summary statistics: the case of admixture.

Vitor C Sousa1, Marielle Fritz, Mark A Beaumont

  • 1Instituto Gulbenkian de Ciência, Rua da Quinta Grande, Oeiras, Portugal. vitorsousa@igc.gulbenkian.pt

Genetics
|February 5, 2009
PubMed
Summary
This summary is machine-generated.

Approximate Bayesian computation (ABC) methods offer a viable alternative to complex population genetics models. Using the full allelic distribution within ABC frameworks provides accurate inferences comparable to traditional methods.

More Related Videos

Optimization of Processing of Tiebangchui with Highland Barley Wine Based on the Box-Behnken Design Combined with the Entropy Method
09:12

Optimization of Processing of Tiebangchui with Highland Barley Wine Based on the Box-Behnken Design Combined with the Entropy Method

Published on: May 19, 2023

Related Experiment Videos

Last Updated: Jun 25, 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

Optimization of Processing of Tiebangchui with Highland Barley Wine Based on the Box-Behnken Design Combined with the Entropy Method
09:12

Optimization of Processing of Tiebangchui with Highland Barley Wine Based on the Box-Behnken Design Combined with the Entropy Method

Published on: May 19, 2023

Area of Science:

  • Population Genetics
  • Computational Biology
  • Statistical Inference

Background:

  • Approximate Bayesian computation (ABC) methods are increasingly used in population genetics for complex demographic models.
  • Traditional ABC methods often rely on carefully selected summary statistics, which can be challenging.
  • Uncertainty remains regarding the performance of ABC methods compared to full-likelihood approaches.

Purpose of the Study:

  • To evaluate the direct use of full allelic distributions within an ABC framework.
  • To compare the performance of ABC with full-likelihood methods using an admixture model.
  • To investigate various aspects of ABC methodology, including distance metrics.

Main Methods:

  • A simulation study was conducted to compare ABC and full-likelihood methods.
  • The study utilized an admixture model involving two parental populations and a hybrid population evolving under drift.
  • The direct use of full allelic distributions in ABC was tested, alongside an examination of distance metrics.

Main Results:

  • ABC methods using the full allelic distribution provided good approximations of posterior distributions.
  • Results demonstrated comparable performance between ABC and full-likelihood methods in the tested admixture model.
  • The choice of distance metric in ABC was investigated for its impact on results.

Conclusions:

  • Directly using allele frequencies in ABC is a feasible approach for population genetics inferences.
  • ABC methods are effective when selecting summary statistics is difficult or full-likelihood methods are computationally prohibitive.
  • This study supports the application of ABC with allele frequency data for complex population genetic models.