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

Haplotype uncertainty in association studies.

F K Mensah1, M S Gilthorpe, C F Davies

  • 1Department of Health Sciences, Epidemiology and Genetics Unit, University of York, York, United Kingdom.

Genetic Epidemiology
|February 27, 2007
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 pilot study of a joint outdoor exercise program for dog owners and dogs.

Scientific reports·2024
Same author

Progression free survival of myeloma patients who become IFE-negative correlates with the detection of residual monoclonal free light chain (FLC) by mass spectrometry.

Blood cancer journal·2024
Same author

Livestock microbial landscape patterns: Retail poultry microbiomes significantly vary by region and season.

Food microbiology·2021
Same author

Mutations in CRBN and other cereblon pathway genes are infrequently associated with acquired resistance to immunomodulatory drugs.

Leukemia·2021
Same author

Exome sequencing of early-onset patients supports genetic heterogeneity in colorectal cancer.

Scientific reports·2021
Same author

Patient-Reported Outcome Measures for Post-mastectomy Breast Reconstruction: A Systematic Review of Development and Measurement Properties.

Annals of surgical oncology·2020
Same journal

Applying Bayesian Multivariable Mendelian Randomisation to Prioritise Candidate Causal Traits From High-Dimensional Data: Illustration From Estimation of the Effect of Maternal Metabolites on Offspring Birthweight.

Genetic epidemiology·2026
Same journal

Individualized Bayesian Inference Identifies Novel Genetic Variants for Parkinson's Disease.

Genetic epidemiology·2026
Same journal

DRIVE v3: Command Line Application for Identity-by-Descent Haplotype Clustering in Large Biobank Scale Data.

Genetic epidemiology·2026
Same journal

Deep Unsupervised Domain Adaptation for Translating Cancer Dependency Maps From Cell Lines to Breast Cancer Tumor Genomics.

Genetic epidemiology·2026
Same journal

Polygenic Risk Scores for Incident Dementia in the Multi-Ethnic Study of Atherosclerosis.

Genetic epidemiology·2026
Same journal

Outcome and Exposure Polygenic Risk Scores Can Help Reduce Information Bias and Selection Bias in Regression Estimates From Biobank Data.

Genetic epidemiology·2026
See all related articles

Accounting for uncertainty in haplotype inference is crucial for population genetic studies. Simple adjustments showed minimal impact on non-Hodgkin lymphoma association analyses, but simulations revealed methods to mitigate bias in complex genetic regions.

Area of Science:

  • Population Genetics
  • Genetic Epidemiology
  • Bioinformatics

Background:

  • Haplotype inference from genotype data is fundamental in population genetic association studies.
  • Acknowledging and addressing uncertainty in haplotype inference is recognized as critical for study validity.

Purpose of the Study:

  • To evaluate the effectiveness of simple correction methods for haplotype inference uncertainty.
  • To identify genetic region characteristics susceptible to haplotype uncertainty influences.
  • To assess bias mitigation strategies in haplotype inference, particularly in case-control studies.

Main Methods:

  • Utilized PHASE methodology for haplotype inference.
  • Conducted case-control association analyses for non-Hodgkin lymphoma.

Related Experiment Videos

  • Employed simulations to model varying degrees of haplotype uncertainty, linkage, and missing genotype data.

    • Main Results:

    • Minimal impact of uncertainty adjustment was observed in non-Hodgkin lymphoma association analyses.
    • Bias in haplotype inference can be avoided by using haplotype probabilities or multiple imputation.
    • Separate inference for case and control populations is essential for these bias mitigation methods.

    Conclusions:

    • While simple adjustments had limited effect, robust methods like haplotype probabilities and multiple imputation can effectively manage haplotype uncertainty.
    • Multiple imputation offers the advantage of incorporating uncertainty into confidence interval estimations.
    • Findings provide guidance for handling haplotype inference complexity in large, marker-rich genetic regions.