TY - JOUR
T1 - HISSTA
T2 - a human in situ single-cell transcriptome atlas
AU - Yu, Jiwon
AU - Moon, Jiwoo
AU - Kim, Minseo
AU - Han, Gyeol
AU - Jang, Insu
AU - Lim, Jinyoung
AU - Lee, Seungmook
AU - Yoon, Seok Hwan
AU - Park, Woong Yang
AU - Lee, Byungwook
AU - Lee, Sanghyuk
N1 - Publisher Copyright:
© The Author(s) 2025. Published by Oxford University Press.
PY - 2025/4/1
Y1 - 2025/4/1
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/105003396358
U2 - 10.1093/bioinformatics/btaf142
DO - 10.1093/bioinformatics/btaf142
M3 - Article
C2 - 40163697
AN - SCOPUS:105003396358
SN - 1367-4803
VL - 41
JO - Bioinformatics
JF - Bioinformatics
IS - 4
M1 - btaf142
ER -
