epihet

epihet quantifies and analyzes intra-tumoral epigenetic heterogeneity from bisulfite sequencing data as an R/Bioconductor package, producing locus-level metrics and co-epigenetic networks to identify epiallelic variation and candidate biomarkers.

Key Features:

• Epigenetic heterogeneity calculation: Calculates intra-tumoral epigenetic heterogeneity from bisulfite sequencing data by tracking epipolymorphism, the proportion of discordantly methylated sequencing reads (PDR), and Shannon entropy values at shared epialleles between samples.
• Differential epigenetic heterogeneity analysis: Identifies statistically significant loci that differ in epigenetic heterogeneity between cancerous and normal tissues.
• Data visualization: Generates heatmaps, box plots, PCA plots, t-SNE plots, and MA plots to represent heterogeneity metrics and comparison results.
• Network analysis workflow: Transforms cancer-specific differential epigenetic heterogeneity loci into biological-function insights and candidate clinical biomarkers via network analysis.
• Co-epigenetic heterogeneity network construction: Constructs co-epigenetic heterogeneity networks and modules to reveal interconnected loci and their potential functional relationships.

Scientific Applications:

• Cancer epigenetics: Applied to characterize intra-tumoral epigenetic allelic heterogeneity as an indicator of tumor population fitness and transcriptional deregulation.
• Acute myeloid leukemia (AML) analysis: Demonstrated to reveal significant differential epigenetic heterogeneity loci when comparing AML samples with normal controls.

Methodology:

Processes bisulfite sequencing data to calculate epipolymorphism, PDR, and Shannon entropy at shared epialleles, performs differential epigenetic heterogeneity analysis to identify significant loci, and integrates these calculations with visualization and co-epigenetic heterogeneity network construction.