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

Quantitative trait locus analysis of longitudinal quantitative trait data in complex pedigrees.

Stuart Macgregor1, Sara A Knott, Ian White

  • 1Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3JT, United Kingdom. macgregors@cf.ac.uk

Genetics
|July 16, 2005
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

Optical convolutional spectrometer.

Nature photonics·2026
Same author

The effects of climate and land cover on hazel dormouse (Muscardinus avellanarius) body mass over space and time.

Scientific reports·2026
Same author

Phenotyping the Structure and Function of the Heart of Elite Sailors: Implications for Pre-Participation Cardiac Screening.

Journal of cardiovascular development and disease·2026
Same author

Drug persistence of first- and advanced-line therapy for chronic inflammatory pouch disorders: A prospective cohort spanning sequential treatment lines.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver·2025
Same author

A decade of innovation: the journey of Microsystems & Nanoengineering on its 10th anniversary.

Microsystems & nanoengineering·2025
Same author

Environmental and population correlates of variation in short torpor use by wild hazel dormice (Muscardinus avellanarius).

Oecologia·2025

Analyzing longitudinal data with random regression and covariance functions (CFs) improves genetic analysis of traits like blood pressure. This method enhances quantitative trait locus (QTL) detection power over traditional techniques.

Area of Science:

  • Genetics
  • Biostatistics

Background:

  • Quantitative traits like blood pressure change over time but are often analyzed at a single point.
  • Understanding the genetic basis requires analyzing longitudinal data, which is complex due to pedigrees and genetic markers.

Purpose of the Study:

  • To propose and evaluate a flexible random regression technique for longitudinal quantitative trait locus (QTL) analyses.
  • To model the relationship between genetic effects across different ages using covariance functions (CFs).

Main Methods:

  • Employed a random regression estimation technique incorporating covariance functions (CFs) to model genetic effects over time.
  • Utilized simulated data to test the proposed method's efficacy in characterizing changes in genetic effects.

Main Results:

Related Experiment Videos

  • Covariance functions (CFs) effectively characterize the change in genetic effects over time.
  • Modeling age-related changes in genetic effects significantly increased power for QTL detection compared to univariate or repeated measures analyses.

Conclusions:

  • The proposed CF-based random regression technique offers a powerful approach for longitudinal QTL analysis.
  • This method facilitates efficient multivariate genetic analyses for human and natural populations using longitudinal data.