Abstract Recent studies have emphasized the importance of single-cell spatial biology, yet available assays for spatial transcriptomics have limited gene recovery or low spatial resolution. Here we introduce CytoSPACE, a method for aligning single-cell and spatial transcriptomes via convex linear optimization. Across diverse platforms and tissue types, we show that CytoSPACE outperforms previous methods with respect to noise-tolerance, accuracy, and efficiency, enabling improved analysis of spatial transcriptomics data at single-cell resolution.

Robust alignment of single-cell and spatial transcriptomes with CytoSPACE