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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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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...

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Related Experiment Video

Updated: Jul 3, 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

pGWAS-Portal: a comprehensive online platform for integrative post-genome-wide association study analysis.

Zijun Zhu¹, Hailong Li¹, Xin Wang¹

¹College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, 150081, China.

|July 2, 2026

Summary

pGWAS-Portal is a new platform that unifies genome-wide association study (GWAS) analysis. It streamlines complex trait genetics research, offering six modules for enhanced genetic discovery and translational potential.

Keywords:

GWAS Genetics Integrated strategy One-stop platform

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Last Updated: Jul 3, 2026

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

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Area of Science:

Genetics and Bioinformatics
Complex Trait Analysis
Computational Biology

Background:

Genome-wide association studies (GWAS) have significantly advanced our understanding of complex traits.
Existing tools for post-GWAS analysis are fragmented, limiting efficiency and translational potential.
A unified platform is needed to integrate diverse analytical methodologies for comprehensive genetic insights.

Purpose of the Study:

To develop pGWAS-Portal, an integrated platform for streamlining and enhancing post-GWAS analyses.
To provide a user-friendly, comprehensive solution for exploring genetic architecture and molecular mechanisms of complex traits.
To facilitate translational research by connecting genetic findings to biological insights and clinical applications.

Main Methods:

Development of a unified web-based platform, pGWAS-Portal.
Integration of six progressive analytical modules: Heritability Estimation, Enrichment Pattern analysis, Cross-Trait Analysis, Fine-Mapping, Correlation and Causality assessment, and Risk Factors Identification.
Implementation of over thirty established algorithms within a cohesive framework.

Main Results:

pGWAS-Portal offers a comprehensive suite of tools for post-GWAS analysis in a single platform.
The platform covers key analytical steps from heritability estimation to causal relationship inference.
It provides a user-friendly interface and is freely accessible as a web server.

Conclusions:

pGWAS-Portal addresses the need for an integrated approach to post-GWAS analysis.
The platform enhances the efficiency and translational potential of genetic research on complex traits.
It serves as a valuable resource for researchers investigating the genetic basis of phenotypes.