Abstract
MOTIVATION: Spatial transcriptomics holds great promise for revolutionizing biology and medicine by providing gene expression profiles with spatial information. Until recently, spatial resolution has been limited, but advances in high-throughput in situ imaging technologies now offer new opportunities by covering thousands of genes at a single-cell or even subcellular resolution, necessitating databases dedicated to comprehensive coverage and analysis with user-friendly intefaces. RESULTS: We introduce the HISSTA database, which facilitates the archival and analysis of in situ transcriptome data at single-cell resolution from various human tissues. We have collected and annotated spatial transcriptome data generated by MERFISH, CosMx SMI, and Xenium techniques, encompassing 112 samples and 28 million cells across 16 tissue types from 63 studies. To decipher spatial contexts, we have implemented advanced tools for cell type annotation, spatial colocalization, spatial cellular communication, and niche analyses. Notably, all datasets and annotations are interactively accessible through Vitessce, allowing users to focus on regions of interest and examine gene expression in detail. HISSTA is a unique database designed to manage the rapidly growing dataset of in situ transcriptomes at single-cell resolution. Given its comprehensive data content and advanced analysis tools with interactive visualizations, HISSTA is poised to significantly impact cancer diagnosis, precision medicine, and digital pathology. AVAILABILITY AND IMPLEMENTATION: HISSTA is freely accessible at https://kbds.re.kr/hissta/. The source code is available at https://doi.org/10.5281/zenodo.14904523.