Quantitative comparison of within-sample heterogeneity scores for DNA methylation data

Area of Science:

• Epigenetics
• Genomics
• Bioinformatics

Background:

• DNA methylation is a key epigenetic regulator of cellular identity.
• Current methods often overlook DNA methylation variability within cell populations.
• Within-sample heterogeneity (WSH) scores quantify this variability in sequencing data.

Purpose of the Study:

• To systematically compare existing WSH scores.
• To propose novel WSH scores.
• To provide guidance on selecting WSH scores for various biological scenarios.

Main Methods:

• Comparison of four published WSH scores using simulated and public datasets.
• Development and validation of two new WSH scores.
• Application of WSH scores to Ewing sarcoma methylation data.

Main Results:

• Most WSH scores effectively detect DNA methylation heterogeneity.
• Differences in susceptibility to technical biases were observed among scores.
• DNA methylation heterogeneity provides complementary information to average methylation levels.
• WSH analysis identified potential novel disease-associated loci in Ewing sarcoma.

Conclusions:

• WSH scores are valuable for analyzing DNA methylation variance.
• These scores can uncover genomic loci missed by traditional statistics.
• An R-package is provided for integrating WSH scores into analysis workflows.