CellMap: precision mapping of cellular landscape in spatial transcriptomics

Integrating single-cell RNA sequencing and spatial transcriptomics is the current imperative to manually explore the landscape of cellular mixtures. Herein, we developed CellMap (https://github.com/liuhong-jia/CellMap), a computational tool that allows spatial transcriptomic spots to be resolved at single-cell resolution. CellMap combines strategies that incorporate the co-linearity of seed genes, the random forest model, and the linear assignment algorithm to achieve optimal assignment of single cells to spatial spots. Using comprehensive benchmarking across various platforms and tissue types, we demonstrated that CellMap outperforms existing methods.