Cells in the body share the same genome, yet acquire different identities by activating distinct combinations of enhancers and promoters. To understand regulatory heterogeneity across cell types and developmental states, this project will develop computational methods to analyse two new assays, scDamID and snTRECseq, which directly record enhancer and promoter activity in single cells across tissues.

Current methods usually infer enhancer activity indirectly from chromatin accessibility or histone modifications as proxy signals, while direct measurements remain limited in throughput or sensitivity. This makes it difficult to determine which enhancers are truly active in individual cells, and how their activity shapes cell identity, state transitions, and tissue development.

The project will benchmark existing single-cell analysis tools and develop statistical models tailored to sparse enhancer and promoter activity data. By combining snTRECseq and scDamID, the resulting software will help reconstruct cell-state-specific regulatory networks and identify disease-relevant regulatory mechanisms.

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