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

What is Population Genetics?01:25

What is Population Genetics?

A population is composed of members of the same species that simultaneously live and interact in the same area. When individuals in a population breed, they pass down their genes to their offspring. Many of these genes are polymorphic, meaning that they occur in multiple variants. Such variations of a gene are referred to as alleles. The collective set of all the alleles within a population is known as the gene pool.While some alleles of a given gene might be observed commonly, other variants...
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,...
Chi-square Analysis02:46

Chi-square Analysis

The chi-square test is a statistical hypothesis test. It is used to check whether there is a significant difference between an expected value and an observed value. In the context of genetics, it enables us to either accept or reject a hypothesis, based on how much the observed values deviate from the expected values.
The chi-square test was developed by Pearson in 1990.
The first step of performing a Chi-square analysis is to establish a null hypothesis, which assumes that there is no real...
Stratified Sampling Method01:16

Stratified Sampling Method

Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
Sample Proportion and Population Proportion01:20

Sample Proportion and Population Proportion

Collecting samples or responses from an entire population takes significant time and effort, so a researcher collects responses from only a sample of that population. Suppose a study needs to collect information about a specific mobile application. After sample collection, the researcher analyzes the data and discovers that most individuals in the sample use that specific mobile application. The sample proportion measures the number of individuals in a sample who either use or don't use the...
Sample Size Calculation01:19

Sample Size Calculation

Knowledge of the sample size is the first requirement to conduct random sampling or an experiment. The sample size is the total number of units, observations, or groups (in some cases) used to get the data to estimate a population parameter. As the name suggests, the sample size is that of the sample drawn from the population and differs from the population size.
The sample size for the given experiment or sampling effort is fundamental to any study design. Sample size decides the number of...

You might also read

Related Articles

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

Sort by
Same author

Global diversity analysis of plant-associated <i>Pseudopithomyces</i> fungi reveals a new species producing the toxin associated with facial eczema in livestock: <i>Pseudopithomyces toxicarius sp. nov</i>.

Studies in mycology·2026
Same author

[Epidemiological Characteristics and infection sources of cholera in China from 2005 to 2024].

Zhonghua yu fang yi xue za zhi [Chinese journal of preventive medicine]·2025
Same author

[Results of the cancer screening program in urban areas in Shaanxi province of China, 2019-2020].

Zhonghua zhong liu za zhi [Chinese journal of oncology]·2024
Same author

[Clinical prognostic analysis of 124 adult patients with hemophagocytic lymphohistiocytosis: a multicenter retrospective study of the Huaihai Lymphoma Working Group].

Zhonghua xue ye xue za zhi = Zhonghua xueyexue zazhi·2021
Same author

<i>Fusarium</i>: more than a node or a foot-shaped basal cell.

Studies in mycology·2021
Same author

A GIANT NON-FUNCTIONAL PARATHYROID CYST.

Acta endocrinologica (Bucharest, Romania : 2005)·2020

Related Experiment Video

Updated: Jul 7, 2026

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
10:17

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

Published on: November 3, 2010

Estimating the total number of alleles using a sample coverage method.

S P Huang1, B S Weir

  • 1Program in Statistical Genetics, Department of Statistics, North Carolina State University, Raleigh, North Carolina 27695-7566, USA.

Genetics
|December 1, 2001
PubMed
Summary

Estimating the total number of alleles requires advanced methods beyond simple observation. The sample coverage method offers a more accurate allele count, especially with unequal frequencies, improving genetic diversity estimates.

More Related Videos

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

Frequency and Distribution of Crossovers in Caenorhabditis elegans Meiosis by SNP Genotyping using Real-time PCR
06:18

Frequency and Distribution of Crossovers in Caenorhabditis elegans Meiosis by SNP Genotyping using Real-time PCR

Published on: July 11, 2025

Related Experiment Videos

Last Updated: Jul 7, 2026

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
10:17

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

Published on: November 3, 2010

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

Frequency and Distribution of Crossovers in Caenorhabditis elegans Meiosis by SNP Genotyping using Real-time PCR
06:18

Frequency and Distribution of Crossovers in Caenorhabditis elegans Meiosis by SNP Genotyping using Real-time PCR

Published on: July 11, 2025

Area of Science:

  • Population Genetics
  • Bioinformatics
  • Statistical Genetics

Background:

  • Accurate estimation of allele number is crucial for population genetics.
  • Previous methods often underestimate the true number of alleles at a locus.
  • Estimating species richness shares similarities with estimating allele richness.

Purpose of the Study:

  • To apply the sample coverage method for estimating the total number of alleles in a population.
  • To address the challenge of unequal allele frequencies in estimation.
  • To compare the effectiveness of this method against simple observed counts.

Main Methods:

  • Utilized the sample coverage method developed by Chao and Lee (1992).
  • Conducted simulation studies under various population genetic models (recurrent, stepwise, infinite-allele).
  • Assessed accuracy with varying sample sizes and allele frequency distributions.

Main Results:

  • The sample coverage method provides a significantly better estimate of the true allele number than observed counts for reasonable sample sizes.
  • The method's performance was evaluated across recurrent, stepwise, and infinite-allele mutation models.
  • Demonstrated improved accuracy compared to relying solely on observed alleles.

Conclusions:

  • The sample coverage method is a valuable tool for accurately estimating the total number of alleles in a population.
  • This method enhances the characterization of allele frequency distributions and genetic diversity estimates.
  • Potential applications include refining microsatellite allele range estimation.