Spatial transcriptomics is rapidly advancing, routinely producing vast numbers of spatial datasets across large tissue areas 1. Several technologies now offer transcriptomic profiling at microscopic ...

In spatial transcriptomics, tissue samples are randomly positioned. Rotation-sensitive methods can lead to unreliable spatially variable gene (SVG) detection. We highlight their inherent technical ...

The field of spatial transcriptomics utilizes technologies that map gene expression data to specific cellular locations within tissues. While traditional RNA sequencing methods generate quantitative ...

Spatial transcriptomics provides a unique perspective on the genes that cells express and where those cells are located. However, the rapid growth of the technology has come at the cost of ...

Biological systems are inherently three-dimensional—tissues form intricate layers, networks, and architectures where cells interact in ways that extend far beyond a flat plane. To capture the true ...

A team of Vanderbilt researchers has released a new benchmarking study that aims to assist scientists in selecting the most effective methods for analyzing spatial transcriptomics (ST) data. ST ...

Technological development is key to improving the way hematologic cancer is diagnosed and treated. With this vision, the Josep Carreras Leukemia Research Institute is committed to the creation and ...

A collaborative project has created a comprehensive guide to help standardize spatial transcriptomics practices. Spatial transcriptomics provides a unique perspective on the genes that cells express ...

Applying single-cell RNA sequencing has led researchers to be able to profile the entire transcriptome of cells. However, these transcriptomes prove difficult to link back to their original location ...