The function of many biological systems, such as embryos, liver lobules, intestinal villi, and
tumors, depends on the spatial organization of their cells. In the past decade, high …

Spatial transcriptomics is a rapidly growing field that promises to comprehensively
characterize tissue organization and architecture at the single-cell or subcellular resolution …

Spatial omics data are advancing the study of tissue organization and cellular
communication at an unprecedented scale. Flexible tools are required to store, integrate and …

Most spatial transcriptomics technologies are limited by their resolution, with spot sizes
larger than that of a single cell. Although joint analysis with single-cell RNA sequencing can …

The development of spatial transcriptomics (ST) technologies has transformed genetic
research from a single-cell data level to a two-dimensional spatial coordinate system and …

Spatial transcriptomics promises to greatly improve our understanding of tissue organization
and cell–cell interactions. While most current platforms for spatial transcriptomics only offer …

Quantifying RNAs in their spatial context is crucial to understanding gene expression and
regulation in complex tissues. In situ transcriptomic methods generate spatially resolved …

Spatially resolved transcriptomic data demand new computational analysis methods to
derive biological insights. Here, we comment on these associated computational challenges …

RNA hybridization‐based spatial transcriptomics provides unparalleled detection sensitivity.
However, inaccuracies in segmentation of image volumes into cells cause misassignment of …

Motivation Imaging-based spatial transcriptomics has the power to reveal patterns of single-
cell gene expression by detecting mRNA transcripts as individually resolved spots in …