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

Model choice in gene mapping: what and why.

Mikko J Sillanpää1, Jukka Corander

  • 1Rolf Nevanlinna Institute, FIN-00014 University of Helsinki, Finland. mjs@rolf.helsinki.fi

Trends in Genetics : TIG
|June 5, 2002
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

A more complete picture: capturing single nucleotide variant diversity in extended-spectrum beta-lactamase producing <i>Escherichia coli</i> using post-enrichment metagenomics.

Microbial genomics·2026
Same author

Pre-clinical efficacy of a candidate outer membrane vesicle gonococcal vaccine in comparison with 4CMenB.

NPJ vaccines·2026
Same author

Proximal regularization of deep residual neural networks applied to high-dimensional genomic data.

Briefings in bioinformatics·2026
Same author

CRISPR-based environmental detection of Burkholderia pseudomallei identifies sanitation gaps and melioidosis risk in northeast Thailand.

Nature communications·2026
Same author

Bayesian network tool for analyzing the cost-effectiveness of bulk forensic trace DNA profiling.

Journal of forensic sciences·2026
Same author

Strain-level transmission inference across multi-kingdom metagenomic data using TRACS.

Nature microbiology·2026

Selecting the right genetic model is crucial for gene mapping studies. This overview explains popular statistical criteria for choosing genetic models and suggests Bayesian model averaging as a robust alternative.

Area of Science:

  • Genetics
  • Biostatistics
  • Quantitative Genetics

Background:

  • Gene mapping studies require accurate genetic models to understand trait inheritance.
  • Genetic models define the number, position, and effects of genes influencing phenotypes.
  • Model selection involves data assumptions, environmental factors, and the number of quantitative trait loci (QTLs).

Purpose of the Study:

  • To provide an overview of popular statistical criteria for genetic model selection.
  • To explain the principles behind various model selection approaches.
  • To introduce Bayesian model averaging as a robust alternative.

Main Methods:

  • Review of existing statistical criteria for genetic model selection.
  • Explanation of the theoretical underpinnings of these criteria.

Related Experiment Videos

  • Presentation of Bayesian model averaging as a proposed method.

    • Main Results:

    • Several popular statistical criteria for genetic model selection are discussed.
    • The principles guiding these selection procedures are elucidated.
    • Bayesian model averaging is highlighted for its robustness.

    Conclusions:

    • The choice of genetic model is fundamental in gene mapping.
    • Understanding statistical criteria aids in selecting appropriate models.
    • Bayesian model averaging offers a reliable approach for genetic model selection.