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

Software for tag single nucleotide polymorphism selection.

Daniel O Stram1

  • 1Division of Biostatistics and Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA. stram@usc.edu

Human Genomics
|July 12, 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

The Multiethnic Cohort: A Resource for the Study of Genetic and Nongenetic Cancer Risk across Populations.

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology·2026
Same author

The association of epigenetic age acceleration with internal smoking dose, risk of lung cancer, and all-cause mortality in cigarette smokers: the Multiethnic Cohort study.

Clinical epigenetics·2026
Same author

A reanalysis of a genome-wide association study on breast cancer in Asian populations using the SG10K_Health reference panel for imputation: a multi-Centre case-control analysis.

Human molecular genetics·2026
Same author

Racial and ethnic differences in the impact of air pollution on the risk of Alzheimer's disease and related dementias in the Multiethnic Cohort Study.

Environment international·2026
Same author

Exposure to Industrial Air Toxics and Risk of Breast Cancer in California: The Multiethnic Cohort Study.

Journal of occupational and environmental medicine·2026
Same author

Interaction of genetic and lifestyle risk scores on colorectal cancer risk across five racial and ethnic populations.

Journal of the National Cancer Institute·2026
Same journal

Mutational spectrum of SLC26A4 and SLC26A5 associated with hereditary hearing loss in Moroccan families.

Human genomics·2026
Same journal

National genomic projects in Asia and Africa: a review.

Human genomics·2026
Same journal

Analysis of whole-exome sequencing data from nearly 10,000 Iranian individuals: identification of recessive mitochondrial disease variants and proposal of a population-specific carrier screening panel.

Human genomics·2026
Same journal

Replicating lipid micelles: a feasible precursor to the origin of life and the earliest appearance of genomes.

Human genomics·2026
Same journal

Beckwith-Wiedemann spectrum exhibiting a 46,XY karyotype caused by genome-wide paternal uniparental heterodisomy: a case report.

Human genomics·2026
Same journal

Dynamic responses in the human methylome to exertional heat exhaustion, heat injury, and heat stroke.

Human genomics·2026
See all related articles

This study evaluates software for single nucleotide polymorphism (SNP) tagging, comparing block-based and non-block methods. A novel compromise approach shows promise for efficiently selecting optimal tagging SNPs.

Area of Science:

  • Genetics
  • Bioinformatics

Background:

  • Single nucleotide polymorphisms (SNPs) are key genetic markers.
  • SNP tagging aims to select a subset of SNPs that represent others in a region.
  • Efficient SNP tagging is crucial for genome-wide association studies (GWAS) and genetic research.

Purpose of the Study:

  • To review the theoretical basis of SNP tagging.
  • To evaluate freely available software for SNP tagging.
  • To compare the performance of different SNP tagging approaches.

Main Methods:

  • Reviewed theoretical foundations of SNP tagging.
  • Categorized methods into block-based and non-block-based approaches.
  • Analyzed SNP genotype data from the HapMap project using various software tools.

Related Experiment Videos

Main Results:

  • Pairwise R2 methods often select more tagging SNPs than necessary.
  • Block-based methods can exploit linkage disequilibrium but risk over-fitting.
  • A compromise approach, avoiding explicit block analysis, shows potential.

Conclusions:

  • Different SNP tagging strategies have distinct advantages and disadvantages.
  • Software performance varies, impacting the selection of optimal tagging SNP sets.
  • A flexible, compromise approach offers a promising direction for SNP selection.