Jove
Visualize
Contact Us

Related Concept Videos

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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...
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...

You might also read

Related Articles

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

Sort by
Same author

Genetic risk score to enhance glaucoma case detection: a prospective double-blind screening study (EyeLife) in the population-based Lifelines cohort.

European journal of epidemiology·2026
Same author

Polyneuropathy in kidney transplant recipients: a cross-sectional study in Groningen, the Netherlands.

BMJ open·2026
Same author

<i>Special Issue:</i> 13th International Conference on Computational Advances in Bio and Medical Sciences.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same author

Iron Status, Erythropoietin, and Cancer Incidence in the General Population.

European journal of clinical investigation·2026
Same author

Genetic determinants of childhood blood pressure and heart rate in relation to adult health outcomes: the consortium of childhood blood pressure.

European heart journal·2026
Same author

Empirical evaluation of analytic validity of polygenic scores.

Genome medicine·2026
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 Video

Updated: Jul 5, 2026

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Association testing by haplotype-sharing methods applicable to whole-genome analysis.

Ilja M Nolte1, André R de Vries2, Geert T Spijker3

  • 1Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, the Netherlands.

BMC Proceedings
|May 10, 2008
PubMed
Summary

Two new methods, haplotype sharing statistic (HSS) and CROSS test, efficiently identify disease loci by analyzing shared haplotypes. The CROSS test demonstrated superior performance in pinpointing rheumatoid arthritis regions.

More Related Videos

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

Related Experiment Videos

Last Updated: Jul 5, 2026

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

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

Area of Science:

  • Genetics
  • Statistical genetics
  • Computational biology

Background:

  • Identifying disease loci is crucial for understanding genetic contributions to complex diseases.
  • Haplotype analysis offers a powerful approach for fine-mapping genetic variants associated with disease.
  • Existing methods may face limitations in speed and accuracy for large-scale genomic studies.

Purpose of the Study:

  • To introduce and evaluate two novel haplotype-sharing methods: the haplotype sharing statistic (HSS) and the CROSS test.
  • To assess the efficiency and accuracy of HSS and CROSS in identifying disease-associated loci using real and simulated genetic data.
  • To compare the performance of these new methods against conventional association techniques.

Main Methods:

  • Developed the haplotype sharing statistic (HSS) by comparing shared haplotype lengths between cases and controls.
  • Developed the CROSS test to assess haplotype sharing differences between cases and controls against random expectations.
  • Utilized variance estimation from U-statistics for HSS significance and sequential randomization for the CROSS test.
  • Applied methods to Genetic Analysis Workshop 15 datasets, including a rheumatoid arthritis cohort with single-nucleotide polymorphisms (SNPs) and a whole-genome simulated dataset.

Main Results:

  • The CROSS test identified a significant association for rheumatoid arthritis at ~4407 kb in the Problem 2 dataset, supported by HSS and single-marker analysis.
  • The CROSS test exhibited superior significance and signal-to-noise ratio compared to other methods, enabling identification of a 20-kb candidate region.
  • Both HSS and CROSS detected known rheumatoid arthritis regions in the Problem 3 simulated dataset, with the CROSS test yielding the most significant results.
  • Haplotype sharing methods demonstrated enhanced fine-mapping accuracy over standard haplotype association.

Conclusions:

  • Haplotype sharing methods, particularly the CROSS test, are fast, practical, and effective for identifying disease gene loci.
  • The CROSS test shows significant promise for high-resolution mapping of disease-associated regions, outperforming conventional approaches.
  • These methods offer a valuable advancement for genetic association studies and fine-mapping complex diseases.