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

Effective algorithms for tag SNP selection.

Tie-Fei Liu1, Wing-Kin Sung, Yi Li

  • 1School of Computing, National University of Singapore & Institute of Bioengineering and Nanotechnology, Singapore. liutf@comp.nus.edu.sg

Journal of Bioinformatics and Computational Biology
|November 10, 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

Clonal Hematopoiesis and Type 2 Diabetes: A Narrative Review.

Journal of diabetes·2026
Same author

Intermolecular charge transfer in electron-deficient MOFs enhances NIR absorption for photothermal conversion and water evaporation.

Chemical communications (Cambridge, England)·2026
Same author

Intermolecular Charge Transfer in Perylenediimide-Based Crystalline Materials for Near-Infrared Photothermal Conversion and Photocatalytic Organic Transformations.

Inorganic chemistry·2026
Same author

Inhibition of GLUT1 Ameliorates Thickening of the Glomerular Basement Membrane via the Rheb/mTORC1 Pathway in Diabetic Nephropathy.

Diabetes·2026
Same author

Distinct dietary patterns across type 2 diabetes subtypes: Insights from the SMART2D cohort.

European journal of clinical nutrition·2026
Same author

Pathway-Specific Polygenic Risk Scores and Cardiorenal Complications in Asians With Type 2 Diabetes.

Diabetes, obesity & metabolism·2026
Same journal

CNV-ECOD: A copy number variation detection method based on ECOD algorithm using next-generation sequencing data.

Journal of bioinformatics and computational biology·2026
Same journal

ReinVar: A model-free paradigm-based reinforcement learning approach to detect copy number variation.

Journal of bioinformatics and computational biology·2026
Same journal

When pipelines run but coordinates fail: A simple spatial specificity check for false locality in post-GWAS analysis.

Journal of bioinformatics and computational biology·2026
Same journal

Comparative benchmarking of template-based, evolutionary-diffusion, and generative language models for IsPETase structure prediction.

Journal of bioinformatics and computational biology·2026
Same journal

Trap spaces as labelled ideals of SCC posets: A structural-functional theory of reachability in asynchronous boolean networks.

Journal of bioinformatics and computational biology·2026
Same journal

Erratum - DDINet: Drug-drug interaction prediction network based on multi-molecular fingerprint features and multi-head attention centered weighted autoencoder.

Journal of bioinformatics and computational biology·2026
See all related articles

Selecting optimal Tag SNPs for genetic studies is computationally challenging. This research introduces TSSA and TSSD algorithms to efficiently identify informative Tag SNPs, reducing genotyping costs and improving genetic association studies.

Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Single nucleotide polymorphisms (SNPs) are crucial genetic markers for association studies.
  • Current genotyping technology limits the ability to genotype all common SNPs.
  • Linkage disequilibrium allows for the selection of a subset of SNPs (Tag SNPs) to reduce costs.

Purpose of the Study:

  • To address the NP-complete problem of selecting Tag SNPs.
  • To develop algorithms for efficient Tag SNP selection, considering inter-block dependencies.
  • To reduce the size of Tag SNP sets while maintaining strong associations.

Main Methods:

  • Proposed two algorithms: TSSA (A* search) and TSSD (heuristic).
  • Tackled the block-independent Tag SNP selection problem.

Related Experiment Videos

  • Evaluated algorithms on medium-sized and very large SNP datasets.

    • Main Results:

    • TSSA finds optimal Tag SNP solutions for medium-sized problems efficiently.
    • TSSD handles very large SNP datasets and provides near-optimal solutions.
    • Both algorithms effectively address inter-dependencies among SNP blocks.

    Conclusions:

    • TSSA and TSSD offer effective solutions for Tag SNP selection in genetic association studies.
    • The proposed algorithms balance computational efficiency with solution quality.
    • These methods can significantly reduce genotyping costs and improve the feasibility of large-scale genetic studies.