Visualization of the cellular heterogeneity and spatial architecture of the tumor
microenvironment (TME) is becoming increasingly important to understand mechanisms of …

The recent advancement in spatial transcriptomics technology has enabled multiplexed
profiling of cellular transcriptomes and spatial locations. As the capacity and efficiency of the …

Molecular profiling of single cells has advanced our knowledge of the molecular basis of
development. However, current approaches mostly rely on dissociating cells from tissues …

Studies with temporal or spatial resolution are crucial to understand the molecular dynamics
and spatial dependencies underlying a biological process or system. With advances in high …

Spatial transcriptomic studies are becoming increasingly common and large, posing
important statistical and computational challenges for many analytic tasks. Here, we present …

Currently available single-cell omics technologies capture many unique features with
different biological information content. Data integration aims to place cells, captured with …

Spatial transcriptomic studies are reaching single-cell spatial resolution, with data often
collected from multiple tissue sections. Here, we present a computational method, BASS …

The growing availability of single-cell and spatially resolved transcriptomics has led to the
development of many approaches to infer cell–cell communication, each capturing only a …

Spatially resolved transcriptomics (SRT)-specific computational methods are often
developed, tested, validated, and evaluated in silico using simulated data. Unfortunately …

Single-cell and spatial transcrip-tomics illuminate complementary features of tissues.
Computational integration can synergize these technologies to resolve cell types and …