HISSTA: a human in situ single-cell transcriptome atlas

• DOI: 10.1093/bioinformatics/btaf142
• Publication Date: 2025-03-29T22:37:59Z
• Authors: Jiwon Yu; Jiwoo Moon; Minseo Kim; Gyeol Han; Insu Jang; Jinyoung Lim; Seungmook Lee; Seok-Hwan Yoon; Woong-Yang Park; Byungwook Lee; Sanghyuk Lee
• Keywords: DECIPHER

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