CpGtools

CpGtools analyzes DNA methylation data from bisulfite sequencing and Illumina methylation arrays to annotate, classify, and compare CpG methylation patterns for epigenetic analysis.

Key Features:

• CpG Position Modules: Examine genomic positions of CpGs, associate genomic and epigenomic features with specified CpGs, and generate DNA motif logos that highlight motifs enriched within specific genomic contexts.
• CpG Signal Modules: Analyze DNA methylation values using PCA and t-SNE, apply Bayesian Gaussian mixture modeling to classify CpG sites as fully methylated, partially methylated, or unmethylated, profile average methylation across genomic regions, and produce bean plots and violin plots.
• Differential CpG Analysis Modules: Identify differentially methylated CpGs between groups using Fisher's Exact Test, Student's t-test, ANOVA, non-parametric tests, linear regression, logistic regression, beta-binomial regression, and Bayesian estimation.

Scientific Applications:

• Genomic Annotation: Associate CpGs with genomic features and epigenomic annotations to interpret functional context.
• Epigenetic Profiling: Quantify and visualize methylation levels across regions and CpG sites to characterize epigenetic states.
• Comparative Studies: Detect and characterize differential methylation between experimental groups for studies in disease mechanisms, development, and environmental effects on gene regulation.

Methodology:

Association of CpGs with genomic and epigenomic features; generation of DNA motif logos; dimensionality reduction via PCA and t-SNE; Bayesian Gaussian mixture modeling for CpG classification; regional methylation profiling and visualization with bean plots and violin plots; statistical testing using Fisher's Exact Test, Student's t-test, ANOVA, non-parametric tests, linear regression, logistic regression, beta-binomial regression, and Bayesian estimation.