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DNA Microarrays

DNA Microarrays

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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Updated: Nov 30, 2025

Genome-Wide Analysis of DNA Methylation in Gastrointestinal Cancer

Genome-Wide Analysis of DNA Methylation in Gastrointestinal Cancer

Published on: September 18, 2020

MADA: a web service for analysing DNA methylation array data.

Xinyu Hu¹, Li Tang¹, Linconghua Wang¹

¹School of Computer Science and Engineering, Central South University, Changsha, China.

BMC Bioinformatics

|November 18, 2020

Summary

This summary is machine-generated.

This study introduces MADA, a web service for analyzing DNA methylation array data. MADA simplifies complex bioinformatics tasks, making methylation analysis accessible to researchers without extensive computational expertise.

Keywords:

DNA methylation Differential methylation analysis Downstream analysis Normalization

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Area of Science:

Genomics
Epigenetics
Bioinformatics

Background:

DNA methylation is crucial in human biological processes and diseases.
Illumina Infinium methylation arrays are a key technology for genome-wide methylation analysis.
Reliable workflows are needed for analyzing methylation array data.

Purpose of the Study:

To develop a comprehensive web service for DNA methylation array data analysis.
To provide a user-friendly platform for researchers with limited bioinformatics skills.

Main Methods:

Developed MADA, a web service encompassing pre-processing, batch effect correction, differential methylation analysis, and downstream analysis.
Integrated visualization tools for analysis results.
Included a customization function for user-defined workflows.

Main Results:

MADA successfully handles the complete methylation array data analysis pipeline.
The platform offers visualization of pre-processing, differential methylation analysis, and pathway analysis.
A user-friendly graphical interface is provided.

Conclusions:

MADA facilitates complex methylation array data analysis for users with limited computational experience.
The web service streamlines the entire workflow from data loading to downstream analysis.
MADA is accessible via a web server for practical application.