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Related Concept Videos

Epistasis Analysis01:09

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...
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...
Genetic Screens02:46

Genetic Screens

Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which result in visible changes...
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...

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Related Experiment Video

Updated: Jun 5, 2026

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

Tools for efficient epistasis detection in genome-wide association study.

Xiang Zhang1, Shunping Huang, Fei Zou

  • 1Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. xiang@cs.unc.edu.

Source Code for Biology and Medicine
|January 6, 2011
PubMed
Summary

We developed efficient software for genome-wide association studies (GWAS) to detect gene-gene interactions. These tools significantly speed up epistasis testing, overcoming computational challenges in genetic research.

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A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
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Related Experiment Videos

Last Updated: Jun 5, 2026

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

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization
08:27

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

Published on: July 27, 2021

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
05:01

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

Published on: July 1, 2020

Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Genome-wide association studies (GWAS) aim to identify genetic factors for complex traits.
  • Epistasis (gene-gene interaction) detection is crucial but computationally intensive at a genome-wide scale.
  • The large number of single nucleotide polymorphism (SNP) pair tests poses a significant computational challenge.

Purpose of the Study:

  • To develop efficient computational tools for genome-wide epistasis detection.
  • To overcome the computational burden associated with large-scale genetic interaction analysis.
  • To provide robust methods for identifying gene-gene interactions in GWAS.

Main Methods:

  • Developed three efficient programs: FastANOVA, COE, and TEAM.
  • Utilized permutation testing to control error rates, including family-wise error rate (FWER) and false discovery rate (FDR).
  • Ensured optimal solution finding and significant acceleration of epistasis detection.

Main Results:

  • The developed programs (FastANOVA, COE, TEAM) enable efficient epistasis testing in various GWAS scenarios.
  • Permutation tests effectively control for family-wise error rate and false discovery rate.
  • Significant speed-up in the process of genome-wide epistasis detection was achieved.

Conclusions:

  • FastANOVA, COE, and TEAM provide efficient solutions for epistasis detection in GWAS.
  • The software facilitates robust control of error rates during genetic interaction analysis.
  • User interfaces and source codes are publicly available for broader research application.