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Related Concept Videos

DNA Microarrays02:34

DNA Microarrays

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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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Genome-wide Association Studies-GWAS01:11

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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.
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Eukaryotes have large genomes compared to prokaryotes. To fit their genomes into a cell, eukaryotic DNA is packaged extraordinarily tightly inside the nucleus. To achieve this, DNA is tightly wound around proteins called histones, which are packaged into nucleosomes that are joined by linker DNA and coil into chromatin fibers. Additional fibrous proteins further compact the chromatin, which is recognizable as chromosomes during certain phases of cell division.
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Updated: Jan 6, 2026

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies
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EWAS Data Hub: a resource of DNA methylation array data and metadata.

Zhuang Xiong1,2,3,4, Mengwei Li1,2,3,4, Fei Yang1,2,3,4

  • 1National Genomics Data Center, Beijing 100101, China.

Nucleic Acids Research
|October 5, 2019
PubMed
Summary

The EWAS Data Hub centralizes DNA methylation array data from over 75,000 samples. This resource aids in discovering methylation biomarkers for complex traits and diseases.

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Area of Science:

  • Genomics
  • Epigenetics
  • Bioinformatics

Background:

  • Epigenome-Wide Association Studies (EWAS) are crucial for understanding the epigenetic basis of complex traits.
  • Significant amounts of DNA methylation array data have been generated by numerous EWAS projects.
  • Existing data is often fragmented, hindering comprehensive analysis.

Purpose of the Study:

  • To establish a centralized, normalized resource for DNA methylation array data.
  • To facilitate the discovery of methylation-based biomarkers.
  • To provide reference DNA methylation profiles across diverse biological contexts.

Main Methods:

  • Collected and integrated DNA methylation array data from 75,344 samples.
  • Applied a normalization method to mitigate batch effects across datasets.
  • Standardized associated metadata for comprehensive analysis.

Main Results:

  • EWAS Data Hub integrates a large-scale collection of DNA methylation data.
  • The hub provides normalized data with standardized metadata.
  • Offers reference profiles for 81 tissues/cell types, 6 ancestry categories, and 67 diseases.

Conclusions:

  • EWAS Data Hub serves as a valuable resource for epigenetic research.
  • It supports the retrieval and discovery of methylation biomarkers for various applications.
  • Promises to advance phenotype characterization, clinical treatment, and healthcare through epigenetics.