Access and execute highly optimized computational biological scripts for genomic, proteomic, and metabolic studies.
Integrate BED methylation data with RNA-seq expression to identify high and low expressed gene patterns.
Visualize distribution of gene expression across CpG density bins (Zero, Low, Medium, High) using boxplots to detect trends.
Explore correlation between CpG count and gene expression levels to identify patterns, clusters, or regulatory relationships.
Analyze methylation effects across gene body, upstream, and downstream regions with regression-based insights across multiple samples.
Visualize methylation patterns across upstream, gene body, and downstream regions. Supports combined and modification-specific (5mC, 5hmC) profiles.