Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Genome-wide Association Studies-GWAS

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 Comparisons

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...

Epistasis Analysis

Epistasis Analysis

Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...

Multiple Allele Traits

Multiple Allele Traits

The Concept of Multiple Allelism

Multiple Allele Traits

Multiple Allele Traits

The Concept of Multiple Allelism

Comparing the Survival Analysis of Two or More Groups

Comparing the Survival Analysis of Two or More Groups

Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and Cox...

You might also read

Related Articles

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

Sort by

Same author

A sleep/wake circuit controls isoflurane sensitivity in Drosophila.

Current biology : CB·2013

Same author

Discordant risk: overweight and cardiometabolic risk in Chinese adults.

Obesity (Silver Spring, Md.)·2013

Same author

Study of the impact of uterine artery embolization (UAE) on endometrial microvessel density (MVD) and angiogenesis.

Cardiovascular and interventional radiology·2013

Same author

Comparative proteomic analysis reveals differentially expressed proteins correlated with fuzz fiber initiation in diploid cotton (Gossypium arboreum L.).

Journal of proteomics·2013

Same author

Sodium intake from various time frames and incident hypertension among Chinese adults.

Epidemiology (Cambridge, Mass.)·2013

Same author

Spatial multi-scale variability of soil nutrients in relation to environmental factors in a typical agricultural region, eastern China.

The Science of the total environment·2013

Search research articles

Related Experiment Video

Updated: Jul 7, 2026

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

Association analysis for large-scale gene set data.

Stefan A Kirov¹, Bing Zhang, Jay R Snoddy

¹Oak Ridge National Laboratory, University of Tennessee, USA.

Methods in Molecular Biology (Clifton, N.J.)

|March 5, 2008

Summary

Computer-assisted analysis helps interpret large gene sets from high-throughput experiments. WebGestalt demonstrates associating gene sets with biological pathways and functional annotations for hypothesis generation.

More Related Videos

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

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

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

Published on: June 21, 2018

Related Experiment Videos

Last Updated: Jul 7, 2026

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

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

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

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

Published on: June 21, 2018

Area of Science:

Genomics
Bioinformatics
Systems Biology

Background:

High-throughput biological experiments generate large gene sets requiring computational interpretation.
Biological interpretation of gene sets is crucial for generating testable hypotheses.
Associating gene sets with biological features like pathways is a key analysis step.

Purpose of the Study:

To explain computer-assisted methods for interpreting large gene sets.
To demonstrate the use of WebGestalt for gene set analysis.
To illustrate the association of gene sets with functional annotations, pathways, publications, and protein domains.

Main Methods:

Utilizing WebGestalt as a case study for gene set analysis.
Explaining the process of associating gene sets with biological features.
Employing statistical methods to evaluate feature associations.

Main Results:

WebGestalt provides a platform for associating gene sets with diverse biological information.
The analysis facilitates the biological interpretation of gene sets.
The approach aids in formulating experimental hypotheses.

Conclusions:

Computer-assisted tools like WebGestalt are essential for interpreting large gene sets.
Associating gene sets with functional annotations and pathways enhances biological understanding.
This analysis supports the generation of experimentally verifiable hypotheses.