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 Concept Videos

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

15.3K
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
15.3K
Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

17.9K
A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
17.9K
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

18.6K
Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
18.6K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Identifying therapeutic drug targets using bidirectional effect genes.

Nature communications·2021
Same author

Association of prenatal organochlorine pesticide-dichlorodiphenyltrichloroethane exposure with fetal genome-wide DNA methylation.

Life sciences·2018
Same author

Epigenome-wide study for the offspring exposed to maternal HBV infection during pregnancy, a pilot study.

Gene·2018
Same author

Association of functional MMP-2 gene variant with intracranial aneurysms: case-control genetic association study and meta-analysis.

British journal of neurosurgery·2018
Same author

Differential methylation is associated with non-syndromic cleft lip and palate and contributes to penetrance effects.

Scientific reports·2017
Same author

Impact of genetically supported target selection on R&D productivity.

Nature reviews. Drug discovery·2017

Related Experiment Video

Updated: Jan 18, 2026

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

10.6K

Efficient selective screening of haplotype tag SNPs.

Xiayi Ke1, Lon R Cardon

  • 1Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK. xiayi@well.ox.ac.uk

Bioinformatics (Oxford, England)
|January 23, 2003
PubMed
Summary

Identifying haplotype tagging SNPs (htSNPs) is crucial for genetic studies. The SNPtagger program efficiently screens for minimal sets of single nucleotide polymorphisms (SNPs) to represent haplotype information in large datasets.

More Related Videos

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
11:35

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Published on: August 21, 2016

13.4K
Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

15.7K

Related Experiment Videos

Last Updated: Jan 18, 2026

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

10.6K
Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
11:35

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Published on: August 21, 2016

13.4K
Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

15.7K

Area of Science:

  • Genetics
  • Bioinformatics

Background:

  • Haplotypes, defined by common single nucleotide polymorphisms (SNPs), are vital for mapping disease genes and human traits.
  • A small subset of SNPs, known as haplotype tagging SNPs (htSNPs), can capture comprehensive haplotype information.
  • Identifying htSNPs is essential for large-scale genetic datasets like the human genome haplotype map.

Purpose of the Study:

  • To introduce SNPtagger, a Java-based program designed for identifying minimal sets of htSNPs.
  • To provide a tool that efficiently screens and selects htSNPs for various user-defined requirements.

Main Methods:

  • Development of a Java-based program named SNPtagger.
  • Implementation of algorithms to screen for minimal sets of SNP markers.
  • Inclusion of user-defined options for marker inclusion/exclusion and presentation of alternative htSNP panels.

Main Results:

  • SNPtagger efficiently identifies minimal sets of htSNPs from large datasets.
  • The program offers flexibility in marker selection based on user needs.
  • Alternative htSNP panels can be generated for final selection.

Conclusions:

  • SNPtagger is an effective computational tool for identifying htSNPs.
  • The software facilitates efficient haplotype analysis in large-scale genetic studies.
  • SNPtagger aids in the selection of optimal SNP sets for genetic mapping and trait analysis.