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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...
Epistasis01:39

Epistasis

In addition to multiple alleles at the same locus influencing traits, numerous genes or alleles at different locations may interact and influence phenotypes in a phenomenon called epistasis. For example, rabbit fur can be black or brown depending on whether the animal is homozygous dominant or heterozygous at a TYRP1 locus. However, if the rabbit is also homozygous recessive at a locus on the tyrosinase gene (TYR), it will have an unshaded coat that appears white, regardless of its TYRP1...
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...

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Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
14:06

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Published on: November 12, 2012

EPIBLASTER-fast exhaustive two-locus epistasis detection strategy using graphical processing units.

Tony Kam-Thong1, Darina Czamara, Koji Tsuda

  • 1Max-Planck-Institute of Psychiatry, Munich, Germany.

European Journal of Human Genetics : EJHG
|December 15, 2010
PubMed
Summary
This summary is machine-generated.

We developed EPIBLASTER, a rapid method for genome-wide epistasis detection in case-control studies. This approach efficiently identifies significant single nucleotide polymorphism (SNP) pair interactions, advancing complex disease pathway understanding.

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Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Epistatic interactions between genetic loci are crucial for understanding complex human diseases.
  • Genome-wide epistasis analysis is computationally intensive, limiting its application.
  • Current methods often require significant marginal effects for single loci.

Purpose of the Study:

  • To develop a rapid and computationally efficient method for genome-wide epistasis detection.
  • To enable the identification of epistatic interactions without requiring substantial marginal effects.
  • To facilitate a more comprehensive understanding of genetic architectures underlying diseases.

Main Methods:

  • Propose EPIBLASTER, a two-step method for case-control studies.
  • Compute differences in Pearson's correlation coefficients between cases and controls for all SNP pairs.
  • Utilize a likelihood ratio test from logistic regression for significant interactions and employ graphical processing units (GPUs) for accelerated computation.

Main Results:

  • EPIBLASTER enables rapid, exhaustive detection of significant SNP pair interactions.
  • The coefficient evaluation stage can be completed in approximately one day for large datasets.
  • The method successfully identifies epistatic interactions independent of marginal effects.

Conclusions:

  • EPIBLASTER significantly reduces the computational burden of genome-wide epistasis analysis.
  • This method facilitates deeper insights into complex disease pathways by uncovering gene-gene interactions.
  • The rapid analysis allows for broader application in genetic association studies.