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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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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

GLAMM: Genome-Linked Application for Metabolic Maps.

John T Bates¹, Dylan Chivian, Adam P Arkin

¹Technologies Division, DOE Joint BioEnergy Institute, Emeryville, CA 94608, USA.

Nucleic Acids Research

|June 1, 2011

Summary

The Genome-Linked Application for Metabolic Maps (GLAMM) provides a user-friendly interface for visualizing and reconstructing metabolic networks. It aids in analyzing experimental data and designing novel pathways, integrating with comparative genomics tools.

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Area of Science:

Systems Biology
Metabolic Engineering
Bioinformatics

Background:

Metabolic networks are crucial for understanding cellular functions.
Reconstructing and visualizing these networks from genomic data is complex.
Integrating experimental data provides deeper biological insights.

Purpose of the Study:

To present the Genome-Linked Application for Metabolic Maps (GLAMM) as a unified web interface.
To facilitate visualization and reconstruction of metabolic networks.
To enable integration of experimental data and design of novel pathways.

Main Methods:

Development of a user-friendly web interface (GLAMM).
Integration with comparative genomics tools from MicrobesOnline.
Utilizing annotated genome data for network reconstruction.

Main Results:

GLAMM offers a unified platform for metabolic network visualization and reconstruction.
The tool allows for the integration of experimental data within metabolic contexts.
It supports the investigation of novel transgenic pathway construction.

Conclusions:

GLAMM simplifies the analysis of metabolic networks.
The application enhances systems biology research by integrating diverse data types.
It is freely available to the scientific community.