National Taiwan University

Ovarian cancer is one of the most deadly diseases for women. The curation of a genomic database for ovarian cancer is crucial for the understanding of its molecular heterogeneity. Many studies have obtained single cell RNA sequencing (scRNA-seq) data for ovarian cancer under different experimental settings. The curation of a scRNA-seq database may provide the field with a rich resource to facilitate future research. In this study, we gathered 44 publicly available scRNA-seq datasets from GEO, and annotated each dataset based on various specifications such as species, cluster counts, cell counts, and patient numbers with the incorporation generative AI. Ultimately, we envision to construct a comprehensive database of ovarian cancer with query-based user interface to explore the transcriptomic landscape at the single cell resolution.