HIDF: Integrating Tree-Structured scRNA-seq Heterogeneity for Hierarchical Deconvolution of Spatial Transcriptomics.

ABSTRACT: The limited spatial resolution of mainstream spatial transcriptomic technologies captures transcriptomic mixtures from multiple cells per spot, obscuring crucial single-cell information. While numerous methods leverage single-cell RNA sequencing references to infer cellular composition from ST data, they primarily rely on fixed cell type labels, overlooking the intrinsic hierarchical heterogeneity (subtypes within broad types) of cellular populations and its association with spatial organization. To address this limitation, HIDF, a Hierarchical Iterative Deconvolution Framework is proposed. HIDF progressively resolves cellular heterogeneity from coarse to fine granularity, it employs a hierarchical iterative optimization mechanism guided by the cluster-tree to recover single-cell spatial d

SUBMITTER: Zou Z 

PROVIDER: S-EPMC12948217 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature