While powerful, a significant current limitation of existing approaches is their primary focus on single-cell RNA-seq (scRNA-seq) data. Single cell transcriptomics is well-suited for the assembly and annotation of reference datasets, particularly as differentially expressed gene markers can typically be interpreted to help annotate cell clusters. This has led to the development of high-quality, carefully curated, and expertly annotated references, particularly from consortia including the Human Cell Atlas (HCA10), Human Biomolecular Atlas Project (HuBMAP11), and the Chan Zuckerberg Biohub12. Mapping to these references facilitates data harmonization, standardization of cell ontologies and naming schemes, and comparison of scRNA-seq datasets across experimental conditions and disease states.
