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

Genotyping error detection through tightly linked markers.

Guohua Zou1, Deyun Pan, Hongyu Zhao

  • 1Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, Connecticut 06520-8034, USA.

Genetics
|July 23, 2003
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 bacterial ally for nitrogen-fixing biofilm: enhancing the rhizosphere colonization of <i>Stutzerimonas stutzeri</i> A1501 with surfactin-producing <i>Bacillus velezensis</i> BRI3.

Applied and environmental microbiology·2026
Same author

Electro-driven aerobic biological nitrogen fixation for protein and ammonium production by Azotobacter vinelandii with sucrose as the sole carbon source.

Bioresource technology·2026
Same author

Complete genome sequence of <i>Bradyrhizobium japonicum</i> ACCC 15027.

Microbiology resource announcements·2025
Same author

Optimal prevention and control strategy of infectious disease: Cost-effectiveness analysis based on a modified dynamic model with economic loss.

Infectious Disease Modelling·2025
Same author

Differential Expression Characteristics of Two Isoforms <i>nr5a2f</i> and <i>nr5a2m</i> in Gonadal Differentiation of Chinese Giant Salamanders, <i>Andrias davidianus</i>.

Animals : an open access journal from MDPI·2025
Same author

Robust model averaging approach by Mallows-type criterion.

Biometrics·2024
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
Same journal

Identification of two Cryptococcus neoformans heme transporters involved in Fhb1-mediated nitrosative stress protection in a fission yeast model.

Genetics·2026
Same journal

Analysis of a hypomorphic mei-P26 mutation reveals coordination between developmental programming of germ cells and meiotic chromosome dynamics.

Genetics·2026
Same journal

Neural and Genetic Mechanisms Regulating Copulation Latency in Male Drosophila melanogaster.

Genetics·2026
See all related articles

Identifying genotyping errors is crucial for mapping complex disease genes. Jointly analyzing multiple markers in nuclear families significantly improves error detection rates, especially with more children and population haplotype data.

Area of Science:

  • Genetics
  • Bioinformatics
  • Statistical genetics

Background:

  • Genotyping errors pose a significant challenge in genetic studies, particularly for complex disease gene mapping.
  • Current methods often analyze markers individually, overlooking the potential of joint analysis for error detection.

Purpose of the Study:

  • To investigate the effectiveness of jointly analyzing multiple, tightly linked markers for detecting genotyping errors in nuclear families.
  • To identify families with potential genotyping errors, even those exhibiting Mendelian consistency.

Main Methods:

  • Utilizing the low recombination rate among tightly linked markers in nuclear families.
  • Comparing error detection rates between family trios and families with multiple children.
  • Calculating the probability of correct genotypes in families showing Mendelian consistency.

Related Experiment Videos

  • Assessing the impact of population haplotype frequencies on error detection.

    • Main Results:

    • Joint analysis of multiple markers significantly increases genotyping error detection rates in nuclear families with multiple children compared to trios.
    • Error detection rates improve with an increased number of children per family.
    • Population haplotype frequencies substantially enhance both error detection rates and the confidence in Mendelian-consistent families.

    Conclusions:

    • Jointly analyzing multiple markers is a powerful strategy for improving genotyping error detection in genetic studies.
    • Incorporating population haplotype data further refines the accuracy of genotyping error identification.
    • This approach aids in identifying families with potential errors, crucial for accurate complex disease gene mapping.