| Description |
Sequencing-based spatial transcriptomic (sST) techniques have undergone rapid development in recent years, enabling unbiased, transcriptome-scale measurements of spatial gene expression. However, these methods have yet to be systematically benchmarked, and the considerable variability across technologies and datasets complicates the establishment of evaluation standards. To address this, we have developed a set of reference tissues with well-defined histological structures, utilizing them to generate data and assess six sST. Despite variations in resolution, capture efficiency, and spatial precision, spatial transcriptomic data exhibit characteristics distinct from single-cell RNAseq data, such as enhanced capabilities for capturing certain genes, along with more pronounced blood contamination. This study aims not only to guide biologists in method selection but also to build a consensus on evaluation criteria, establish a framework for future benchmarking, and provide gold standards for the assessment of computational tools. |
