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 Experiment Videos

The variance of sample heterozygosity.

B S Weir1, J Reynolds, K G Dodds

  • 1Department of Statistics, North Carolina State University, Raleigh 27695-8203.

Theoretical Population Biology
|February 1, 1990
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Real-world insights into young-onset gastroesophageal adenocarcinoma: an all-Ireland population-based cancer registry analysis.

ESMO gastrointestinal oncology·2026
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

[Defining healthcare services: A practical guide to the process based on lessons learned].

Journal of healthcare quality research·2026
Same author

Dermal wipe sampling method development and validation for semivolatile and nonvolatile flame-retardant compounds TBBPA and TPP for use in occupational exposure assessments.

Journal of occupational and environmental hygiene·2025
Same author

Response adaptive salvage treatment with daratumumab-lenalidomide-dexamethasone for newly diagnosed transplant-eligible multiple myeloma patients failing front-line bortezomib-based induction therapy-ALLG MM21.

British journal of haematology·2024
Same author

[Operational planning of health services: How do we make it possible?]

Journal of healthcare quality research·2024

This study analyzes sample heterozygosity variance across various population genetics scenarios. Increasing loci scored is more effective than increasing individuals sampled for drift/mutation balance, but the reverse is true for mixed mating systems.

Area of Science:

  • Population Genetics
  • Evolutionary Biology
  • Quantitative Genetics

Background:

  • Sample heterozygosity is a key metric in population genetics for understanding genetic diversity.
  • The variance of sample heterozygosity is influenced by multiple factors including mating systems, allele frequencies, and population size.
  • Previous studies have explored heterozygosity but often with simplified assumptions about population structure.

Purpose of the Study:

  • To investigate the factors influencing the variance of sample heterozygosity across diverse population genetic models.
  • To compare the relative impacts of sampling individuals versus sampling loci on heterozygosity variance.
  • To develop methods for estimating heterozygosity variance, particularly for unbalanced datasets.

Main Methods:

Related Experiment Videos

  • Theoretical analysis of heterozygosity variance under different population genetic models.
  • Consideration of factors such as mating systems (selfing, random mating), mutation-drift balance, and linkage.
  • Development of estimation techniques for unbalanced sampling designs.

    • Main Results:

    • Variance is dependent on mating system sampling, loci scored, individuals sampled, allele distributions, and linkage.
    • For unlinked loci in drift/mutation balance, increasing loci scored reduces variance more than increasing individuals sampled.
    • For infinite populations with mixed self and random mating, increasing individuals sampled reduces variance more than increasing loci scored.

    Conclusions:

    • The relative importance of sampling individuals versus loci depends critically on the population genetic model.
    • Understanding these dependencies is crucial for accurate estimation of genetic diversity and evolutionary parameters.
    • Methods for handling unbalanced data are essential for real-world population genetic studies.