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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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Single Nucleotide Polymorphisms-SNPs

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A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...

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Updated: May 30, 2026

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

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

Published on: July 1, 2020

Haplo2Ped: a tool using haplotypes as markers for linkage analysis.

Feng Cheng¹, Xianglong Zhang, Yinan Zhang

¹Laboratory of Disease Genomics and Individualized Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, No.7 Beitucheng West Road, Beijing 100029, PR China.

BMC Bioinformatics

|August 23, 2011

Summary

This summary is machine-generated.

Haplo2Ped transforms single nucleotide polymorphism (SNP) data into haplotype markers for enhanced linkage analysis. This method accurately identifies disease-associated genomic regions, outperforming existing software, especially for complex pedigrees.

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Area of Science:

Genetics
Bioinformatics
Computational Biology

Background:

Single nucleotide polymorphisms (SNPs) offer limited power in genomic linkage analysis due to low heterozygosity.
Haplotype markers, constructed from multiple SNPs, significantly increase heterozygosity and improve linkage statistics.

Purpose of the Study:

To develop Haplo2Ped, a software tool for automated transformation of SNP data into haplotype markers.
To compute logarithm of odds (LOD) scores for regional haplotypes to identify disease-linked genomic regions.

Main Methods:

Automated conversion of SNP data to haplotype markers.
Calculation of LOD scores for homozygous haplotypes within disease-segregating groups.
Generation of hypertext files and 3D visualizations for linkage signal interpretation.

Main Results:

Haplo2Ped successfully and accurately located causative genomic regions in both simulated and real datasets.
The software provides clear visualizations and detailed information on linked regions, candidate genes, and public database links.
Comparative analysis demonstrated Haplo2Ped's high effectiveness compared to existing linkage analysis software.

Conclusions:

Haplo2Ped utilizes haplotype fragments for whole-genome linkage analysis, offering improved accuracy.
Advantages include straightforward output, enhanced accuracy, and superior handling of pedigrees with incomplete penetrance.
Haplo2Ped is freely available for use in genetic research.