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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: Oct 15, 2025

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

Published on: February 24, 2015

NanoMethViz: An R/Bioconductor package for visualizing long-read methylation data.

Shian Su^1,2, Quentin Gouil^1,2, Marnie E Blewitt^1,2

¹Epigenetics and Development Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia.

Plos Computational Biology

|October 25, 2021

Summary

This summary is machine-generated.

Long-read nanopore sequencing enables DNA modification detection. We developed NanoMethViz, an R package, to visualize and analyze these methylation profiles across various genomic features and experimental groups.

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Last Updated: Oct 15, 2025

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

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Published on: February 24, 2015

Methodology for Accurate Detection of Mitochondrial DNA Methylation

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Targeted DNA Methylation Analysis by Next-generation Sequencing

Targeted DNA Methylation Analysis by Next-generation Sequencing

Published on: February 24, 2015

Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

Long-read nanopore sequencing offers unique advantages for detecting modified DNA bases, including 5-methylcytosine.
Existing R/Bioconductor tools lack comprehensive visualization capabilities for nanopore methylation data across diverse experimental groups.

Purpose of the Study:

To develop an R package, NanoMethViz, for effective visualization and analysis of nanopore sequencing methylation profiles.
To provide a user-friendly tool for handling large methylation datasets and exploring patterns at multiple resolutions.

Main Methods:

Developed the NanoMethViz R package compatible with various methylation callers.
Implemented dimensionality reduction for sample-level methylation profile comparison.
Enabled visualization of aggregated methylation profiles for genomic features (genes, CpG islands) and individual read-level patterns (spaghetti plots, heatmaps).

Main Results:

NanoMethViz efficiently handles large nanopore methylation datasets using a compressed format.
The package facilitates exploration of methylation patterns from sample-level relationships to single-read resolution.
Seamless integration with existing Bioconductor methylation analysis tools is achieved.

Conclusions:

NanoMethViz enhances the convenience of handling methylation signals from nanopore sequencing.
The package expands visualization options for nanopore methylation data, aiding biological interpretation.
NanoMethViz supports comprehensive analysis of DNA methylation patterns within the R/Bioconductor ecosystem.