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Tissues are highly complicated with spatial heterogeneity in gene expression. However, the cutting-edge single-cell RNA-seq technology eliminates the spatial information of individual cells, which contributes to the characterization of cell identities. Herein, we propose single-cell spatial position associated co-embeddings (scSpace), an integrative method to identify spatially variable cell subpopulations by reconstructing cells onto a pseudo-space with spatial transcriptome references (Visium, STARmap, Slide-seq, etc.). We benchmark scSpace with both simulated and biological datasets, and demonstrate that scSpace can accurately and robustly identify spatially variated cell subpopulations. When employed to reconstruct the spatial architectures of complex tissue such as the brain cortex, the small intestinal villus, the liver lobule, the kidney, the embryonic heart, and others, scSpace shows promising performance on revealing the pairwise cellular spatial association within single-cell data. The application of scSpace in melanoma and COVID-19 exhibits a broad prospect in the discovery of spatial therapeutic markers.

Microfluidic technologies are reliable methods to obtain uniform and tiny droplets, but their application is limited by the capacity of single microchannel and the difficulty in fabrication and operation of large amounts of parallel droplet generators. Here, we reported a microchannel device equipped with multiple capillaries for rupturing the dispersed fluid, which realized droplet generation frequency up to 40 kHz in a single microchannel. The microchannel was operated under jetting flow, which was robust for controlling the droplet size uniformity; therefore, the device did not need highly precise machinery and accurate installation during fabrication. 30–100 μm droplets with CV