methVisual

methVisual provides exploratory analysis and visualization of DNA methylation data from bisulfite sequencing to investigate methylation patterns and their regulatory implications.

Key Features:

• Data Import and Alignment: Imports DNA methylation sequences and aligns them for downstream analysis.
• Quality Control: Implements comprehensive quality control measures to assess and validate methylation data.
• Visualization Techniques: Generates lollipop plots and co-occurrence displays of methylation patterns across neighboring and distant CpG sites.
• Statistical Analysis: Computes summary statistics of methylation status and performs clustering and correspondence analysis.
• Versatility: Handles bisulfite sequencing data and other data types that can be binary coded for methylation status.
• Implementation: Implemented as an R package within the Bioconductor environment.

Scientific Applications:

• Epigenetic regulation: Analysis of DNA methylation patterns to study epigenetic regulation mechanisms.
• Gene expression regulation: Investigating relationships between methylation and gene expression regulation.
• Disease mechanisms: Exploring methylation changes implicated in disease mechanisms.
• Developmental processes: Studying methylation dynamics during development.
• Multi-omics integration: Combining methylation data with other biological datasets for comprehensive multi-omics studies.

Methodology:

Workflow includes importation and alignment of DNA methylation sequences, followed by quality control, analysis procedures applied to binary-coded (binarized) data, calculation of summary statistics, clustering and correspondence analysis, and visualization via lollipop plots and co-occurrence displays of CpG methylation patterns.