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Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

EWAS: epigenome-wide association study software 2.0.

Jing Xu^1,2, Linna Zhao^1,2, Di Liu^1,2

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

Bioinformatics (Oxford, England)

|March 23, 2018

Summary

This summary is machine-generated.

A new software, EWAS2.0, has been developed to analyze epigenome-wide association studies (EWAS) and identify links between epigenetic variations and diseases. This tool enhances the analysis of DNA methylation data for better disease research.

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

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Published on: July 1, 2020

Area of Science:

Biotechnology
Genomics
Epigenetics

Background:

DNA methylation data is growing exponentially, necessitating advanced analytical tools.
Epigenome-wide association studies (EWAS) are crucial for understanding epigenetic variants in diseases.
Existing EWAS software has not kept pace with the advancements in genome-wide association study (GWAS) tools.

Purpose of the Study:

To develop a user-friendly and powerful software, EWAS2.0, for analyzing epigenome-wide association studies.
To address the limitations of current EWAS software and meet user demands for comprehensive analysis.

Main Methods:

EWAS2.0 performs epigenome-wide single marker association studies.
EWAS2.0 conducts epigenome-wide methylation haplotype (meplotype) association studies.
EWAS2.0 enables epigenome-wide association meta-analysis, incorporating various statistical tests and analyses like chi-square, t-test, and regression models.

Main Results:

EWAS2.0 identifies associations between epigenetic variations and diseases/phenotypes.
The software facilitates the identification of epi-alleles and methylation disequilibrium (MD) blocks.
EWAS2.0 calculates MD coefficients, meplotype frequencies, and Pearson's correlation coefficients, and performs meta-analysis.

Conclusions:

EWAS2.0 is a versatile and convenient tool for analyzing EWAS data.
The software is expected to become widely adopted in the field of epigenome-wide association studies.
EWAS2.0 enhances the capability to uncover epigenetic insights into common diseases and phenotypes.