Efficient gene set analysis for DNA methylation addressing probe dependency and bias.

ABSTRACT:

Motivation

Gene Set Enrichment Analysis (GSEA) is widely used to interpret DNA methylation data by associating differentially methylated sites with biological pathways. However, existing GSEA methods struggle with several challenges in methylation data, including probe dependency, probe number bias, and the complexity of gene-probe mapping. These limitations can lead to biased enrichment results, reduced statistical power, and computational inefficiencies.

Results

We introduce gsGene and gsPG, two novel GSEA methods specifically designed for DNA methylation data. gsGene aggregates association signals at gene level while correcting for probe dependency and probe number bias, enabling more biologically meaningful enrichment analysis. gsPG takes a different approach by conducti

SUBMITTER: Xu Z 

PROVIDER: S-EPMC12341679 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature