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

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...
Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...

You might also read

Related Articles

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

Sort by
Same author

Global diversity analysis of plant-associated <i>Pseudopithomyces</i> fungi reveals a new species producing the toxin associated with facial eczema in livestock: <i>Pseudopithomyces toxicarius sp. nov</i>.

Studies in mycology·2026
Same author

<i>Fusarium</i>: more than a node or a foot-shaped basal cell.

Studies in mycology·2021
Same author

High milk production decreases cow-calf productivity within a highly available feed resource environment.

Translational animal science·2020
Same author

The Alzheimer's Disease Sequencing Project: Study design and sample selection.

Neurology. Genetics·2017
Same author

Exome Sequencing of Extended Families with Alzheimer's Disease Identifies Novel Genes Implicated in Cell Immunity and Neuronal Function.

Journal of Alzheimer's disease & Parkinsonism·2017
Same author

Phylogenetic relationships of eight new <i>Dacrymycetes</i> collected from New Zealand.

Persoonia·2017

Related Experiment Video

Updated: Jul 21, 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

Applying data mining techniques to the mapping of complex disease genes.

W A Czika1, B S Weir, S R Edwards

  • 1SAS Insitute, SAS Campus Drive, Carey, NC 27513, USA.

Genetic Epidemiology
|January 17, 2002
PubMed
Summary

Data mining techniques combined with traditional statistical tests improved genetic analysis. This approach enhanced disease classification and identified more single nucleotide polymorphisms linked to disease.

More Related Videos

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
04:41

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

Published on: January 9, 2020

Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease
08:51

Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease

Published on: September 20, 2024

Related Experiment Videos

Last Updated: Jul 21, 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

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
04:41

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

Published on: January 9, 2020

Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease
08:51

Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease

Published on: September 20, 2024

Area of Science:

  • Genetics
  • Bioinformatics
  • Statistical Genetics

Background:

  • Genetic analysis workshops provide simulated data for methodological development.
  • Traditional statistical tests are standard for analyzing genetic marker association with disease.
  • Data mining offers advanced computational approaches for complex datasets.

Purpose of the Study:

  • To evaluate the integration of data mining with traditional statistical methods for genetic analysis.
  • To assess the utility of SAS ENTERPRISE MINER for genetic association studies.
  • To improve the identification of genetic markers associated with disease status using combined analytical approaches.

Main Methods:

  • Analysis of simulated genetic sequence data from Genetic Analysis Workshop 12.
  • Application of data mining techniques (SAS ENTERPRISE MINER).
  • Comparison with traditional statistical tests for linkage and association.
  • Examination of covariate and genotypic data integration.

Main Results:

  • Combined methods improved the correct classification of individual affection status.
  • The integrated approach identified a greater number of single nucleotide polymorphisms associated with the disease.
  • Enhanced analytical power compared to using classical methods alone.

Conclusions:

  • Integrating data mining with traditional statistical tests offers significant advantages in genetic association studies.
  • This hybrid approach improves both predictive accuracy and the discovery of disease-related genetic markers.
  • SAS ENTERPRISE MINER is a valuable tool for advanced genetic data analysis.