HOMED enables hierarchical and multimodal optimization of DNA methylation deconvolution across tissues

HOMED (Hierarchically Optimized Methylation Deconvolution) improves bulk DNA methylation deconvolution across peripheral blood mononuclear cell, lung, and placental datasets, achieving the highest PCCs and lowest RMSEs.

• Why it matters: Cellular heterogeneity confounds bulk DNA methylation analyses, and reference-based deconvolution methods can miss cell-type hierarchies and generalize poorly across datasets.
• What they did: HOMED integrates cell-lineage hierarchies, single-cell RNA sequencing-guided deconvolution, and paired bulk RNA-seq/DNAm CpG signature optimization, evaluated on simulated and real datasets.
• The result: Across simulated and real peripheral blood mononuclear cell, lung, and placental data, HOMED yields consistently better accuracy, resolution, and cross-tissue generalizability than existing scRNA-seq-guided DNAm deconvolution methods.