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Related Concept Videos

Genetic Screens02:46

Genetic Screens

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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
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Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
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VEGAS2: Software for More Flexible Gene-Based Testing.

Aniket Mishra1, Stuart Macgregor1

  • 1Statistical Genetics Group,QIMR Berghofer Medical Research Institute,Brisbane,Queensland,Australia.

Twin Research and Human Genetics : the Official Journal of the International Society for Twin Studies
|December 19, 2014
PubMed
Summary
This summary is machine-generated.

VEGAS2 is an updated gene-based testing tool that improves upon VEGAS by using 1,000 Genomes data for SNP correlation modeling across autosomes and the X chromosome.

Keywords:
VEGAS

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Area of Science:

  • Genetics
  • Bioinformatics
  • Statistical Genomics

Background:

  • Gene-based tests like VEGAS are crucial for interpreting single nucleotide polymorphism (SNP) Genome-Wide Association Studies (GWAS).
  • Previous VEGAS versions utilized the outdated HapMap2 reference panel and excluded the X chromosome, limiting comprehensive genetic association analysis.
  • The 1,000 Genomes reference set has replaced HapMap2, and GWAS increasingly incorporate the X chromosome.

Purpose of the Study:

  • To introduce VEGAS2, an enhanced gene-based association testing tool.
  • To address limitations of earlier VEGAS versions by incorporating updated reference data and including the X chromosome.
  • To provide flexible gene boundary definition and user-friendly access through web and command-line interfaces.

Main Methods:

  • Developed VEGAS2, an extension of the VEGAS tool.
  • Utilized the 1,000 Genomes reference panel to model SNP correlations across autosomes and the X chromosome.
  • Implemented flexible gene boundary definition options.

Main Results:

  • VEGAS2 models SNP correlations using the more current 1,000 Genomes reference data.
  • VEGAS2 incorporates genetic data from the X chromosome alongside autosomal chromosomes.
  • The tool offers both a web-based interface and a downloadable Linux command-line version.

Conclusions:

  • VEGAS2 provides an improved and more inclusive approach to gene-based association testing.
  • The updated methodology enhances the ability to identify significant gene associations from GWAS data.
  • VEGAS2 offers accessible options for researchers to conduct advanced genetic analyses.