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

Relaxing haplotype block models for association testing.

Natalie Castellana1, Kedar Dhamdhere, Srinath Sridhar

  • 1Computer Science Department, Carnegie Mellon University, 4400 Fifth Avenue, Pittsburgh, PA 15213, USA.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|November 11, 2006
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

Publisher Correction: Integrated Liquid Biopsy and Tumor Tissue Genomic Profiling of Appendiceal Cancer: cfDNA Burden, Mutation Landscapes, and Clinical Outcomes.

Annals of surgical oncology·2026
Same author

Integrated Liquid Biopsy and Tumor Tissue Genomic Profiling of Appendiceal Cancer: cfDNA Burden, Mutation Landscapes, and Clinical Outcomes.

Annals of surgical oncology·2026
Same author

Systematic benchmarking of mass spectrometry-based antibody sequencing reveals methodological biases.

Cell systems·2025
Same author

Deconvolution and phylogeny inference of diverse variant types integrating bulk DNA-seq with single-cell RNA-seq.

Bioinformatics advances·2025
Same author

Intensive Care Unit Monitoring Post-Tonsillectomy in Children with Obstructive Sleep Apnea.

Journal of otolaryngology - head & neck surgery = Le Journal d'oto-rhino-laryngologie et de chirurgie cervico-faciale·2025
Same author

Cell-Free DNA, Tumor Molecular Concordance, and Clinical Correlates of Patients with Cancer Treated in a Large Community Health Care Network.

The Journal of molecular diagnostics : JMD·2025
Same journal

Trust, Reproducibility, and Progress: The Roles of Independent Blind Prediction and Assessment and Benchmarking in Computational Biology.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2026
Same journal

The Evolving Cyberinfrastructure at the National Institutes of Health to Support Data and AI in Biomedical Research.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2026
Same journal

Applications of AI & ML in Biomanufacturing of Cell and Gene Therapies.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2026
Same journal

AI for Health: Leveraging Artificial Intelligence to Revolutionize Healthcare.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2026
Same journal

Workshop Introduction: Advances of AI Methods in Single Cell Spatial Omics.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2026
Same journal

DRIVE-KG: Enhancing variant-phenotype association discovery in understudied complex diseases using heterogeneous knowledge graphs.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2026
See all related articles

Haplotype models, especially block-free ones, offer modest benefits for genetic association studies by detecting correlations near the detectable limit. These models improve genotype-phenotype association analysis with real genome data.

Area of Science:

  • Genetics
  • Bioinformatics
  • Statistical genomics

Background:

  • Genome-wide variation data enables new approaches for genotype-phenotype association studies.
  • Haplotype block models, assuming population-wide low diversity, are popular but may miss useful correlations.
  • Real genome data presents complexities that challenge existing association models.

Purpose of the Study:

  • To evaluate the utility of haplotype-based association testing methods.
  • To compare the effectiveness of haplotype motif models against traditional block models and single-variant approaches.
  • To investigate if relaxing rigid block model assumptions enhances association detection.

Main Methods:

  • Developed an association testing method based on the haplotype motif model.

Related Experiment Videos

  • Compared motif, block, and single-variant models using simulated phenotypes.
  • Utilized both real and simulated genome-wide variation data for analysis.

    • Main Results:

    • Haplotype models provide modest benefits in detecting genetic associations.
    • Block-free haplotype models are particularly useful for identifying correlations near the detection threshold.
    • The haplotype motif model showed utility in association studies with complex genomic data.

    Conclusions:

    • Haplotype models, especially those without strict block boundaries, can improve genotype-phenotype association analysis.
    • The study highlights the value of flexible haplotype models in uncovering subtle genetic correlations.
    • Publicly available genome data facilitates the testing and refinement of association models.