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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...

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Related Experiment Video

Updated: Jun 23, 2026

Fluorescence-microscopy Screening and Next-generation Sequencing: Useful Tools for the Identification of Genes Involved in Organelle Integrity

Fluorescence-microscopy Screening and Next-generation Sequencing: Useful Tools for the Identification of Genes Involved in Organelle Integrity

Published on: April 13, 2012

Generating linkage mapping files from Affymetrix SNP chip data.

M Bahlo¹, C J Bromhead

¹Bioinformatics Division, The Walter and Eliza Hall Institute, Parkville, 3052 VIC, Australia. bahlo@wehi.edu.au

Bioinformatics (Oxford, England)

|May 14, 2009

Summary

This summary is machine-generated.

LINKDATAGEN is a Perl tool that simplifies genetic linkage map creation. It generates input files for multiple mapping tools using HapMap data, aiding genetic analysis.

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Infinium Assay for Large-scale SNP Genotyping Applications

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Published on: November 19, 2013

Area of Science:

Genetics
Bioinformatics
Computational Biology

Background:

Genetic linkage mapping is crucial for understanding genome organization and disease gene identification.
Standardizing input data formats across different genetic mapping software can be challenging.

Purpose of the Study:

To introduce LINKDATAGEN, a novel Perl-based tool for generating linkage mapping input files.
To facilitate the use of data from the 11 HapMap Phase III populations for genetic analysis.

Main Methods:

LINKDATAGEN processes genetic data to create input files compatible with five distinct linkage mapping tools.
The tool incorporates basic error-checking functionalities.
It is designed for easy customization to accommodate specific user preferences in linkage analysis.

Main Results:

Successfully generates input files for multiple genetic linkage mapping software.
Utilizes data from all 11 HapMap Phase III populations, enhancing data accessibility.
Provides a flexible and user-friendly solution for preparing genetic data.

Conclusions:

LINKDATAGEN streamlines the process of preparing genetic data for linkage mapping.
The tool enhances the efficiency of genetic analysis by supporting diverse mapping software and comprehensive population data.
Its customizable nature makes it adaptable for various research needs in genetic studies.