Protocol for inferring cell type relationships and linking genomic annotations to cell type hierarchies using CellWalker2
Single-cell multiomic data reveal cell type-specific regulatory mechanisms, but comparing hierarchies and regulatory programs across related cell types is challenging. Here, we present a protocol for integrating single-cell data to infer cell type relationships and label genomic annotations within cell type hierarchies using CellWalker2, a graph diffusion-based framework. We describe steps for cell labeling; comparing cell type hierarchies; mapping regulatory elements or transcription factors onto cell type hierarchies; and assessing statistical significance, using human blood and brain datasets. For complete details on the use and execution of this protocol, please refer to Hu et al.<sup>1</sup>.
Authors
- Katherine S. Pollard (ORCID: https://orcid.org/0000-0002-9870-6196)
- Pawel F. Przytycki (ORCID: https://orcid.org/0000-0002-3360-6936)
- Zhirui Hu (ORCID: https://orcid.org/0000-0001-6352-4854)
Institutions
- Boston University (US)
- Gladstone Institutes (US)
Publication Details
- Journal
- STAR Protocols
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1016/j.xpro.2025.104235
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.00