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

Bayesian QTL mapping using skewed Student-t distributions.

Peter von Rohr1, Ina Hoeschele

  • 1Departments of Dairy Science and Statistics, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0315, USA.

Genetics, Selection, Evolution : GSE
|April 4, 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

Are Dairy Cow Replacement Decisions Economically Justified? Evidence from Swiss Farms.

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

LXR signaling pathways link cholesterol metabolism with risk for prediabetes and diabetes.

The Journal of clinical investigation·2024
Same author

LXR signaling pathways link cholesterol metabolism with risk for prediabetes and diabetes.

The Journal of clinical investigation·2024
Same author

Associated regions for multiple birth in Brown Swiss and Original Braunvieh cattle on chromosomes 15 and 11.

Animal genetics·2022
Same author

The association between aging-related monocyte transcriptional networks and comorbidity burden: the Multi-Ethnic Study of Atherosclerosis (MESA).

GeroScience·2022
Same author

Monocyte miRNAs Are Associated With Type 2 Diabetes.

Diabetes·2022
Same journal

The mitogenome diversity of Alpine Rendena cattle: new clues on its maternal origin and the complex substructure of haplogroup T3.

Genetics, selection, evolution : GSE·2026
Same journal

Genomic partitioning and functional dissection of inbreeding depression for stature in Brown Swiss cattle.

Genetics, selection, evolution : GSE·2026
Same journal

Modest contribution of metabolomic data to genomic prediction of breeding values for feed conversion ratio in pigs.

Genetics, selection, evolution : GSE·2026
Same journal

Determining crossover count and position in two pig lines with different selection histories.

Genetics, selection, evolution : GSE·2026
Same journal

Effect of methylation on genome mutability in cattle.

Genetics, selection, evolution : GSE·2026
Same journal

Genomic selection strategies and their potential to maintain rare alleles and de-novo mutations: a long-term assessment.

Genetics, selection, evolution : GSE·2026
See all related articles

This study introduces a more robust Bayesian quantitative trait loci (QTL) mapping method by using a skewed Student-t distribution instead of the normal distribution. This approach improves accuracy by accounting for non-normal phenotype data, reducing false positives in genetic studies.

Area of Science:

  • Genetics
  • Statistical Genetics
  • Bioinformatics

Background:

  • Quantitative trait loci (QTL) mapping commonly assumes normal distributions for phenotypes.
  • Deviations from normality can result in false positive QTL detections.
  • Existing Bayesian methods may lack robustness when these assumptions are violated.

Purpose of the Study:

  • To enhance the robustness of Bayesian QTL mapping methods.
  • To address issues arising from non-normally distributed phenotypes in QTL analysis.
  • To introduce a flexible distribution accommodating skewness and heavy tails.

Main Methods:

  • Replaced the standard normal distribution for residuals with a skewed Student-t distribution.
  • The skewed Student-t distribution allows for control of skewness and heavy tails via single parameters.

Related Experiment Videos

  • Evaluated the proposed Bayesian method using simulated datasets.

    • Main Results:

    • The skewed Student-t distribution effectively models deviations from normality, including heavy tails and skewness.
    • The enhanced Bayesian method demonstrated improved performance under various simulated error distributions.
    • Reduced false positive rates were observed when using the skewed Student-t distribution.

    Conclusions:

    • The proposed Bayesian QTL mapping method using a skewed Student-t distribution is more robust than traditional methods.
    • This approach offers a significant improvement for genetic studies with non-normal phenotypic data.
    • The method provides a reliable tool for accurate QTL detection in complex genetic analyses.