Jensen, A. E. V.; Crowell, H.; Pascual Reguant, A.; Ruano, I.; Tejpar, S.; Heyn, H.; Nilsson, M.; Marco Salas, S.

Copy number variations (CNVs) drive cancer progression. So far, spatial CNV inference has relied on whole transcriptome-based sequencing technologies. However, advances in image-based spatial transcriptomics (iST) now enable high-plex gene measurement in situ. Here, we introduce an approach that adapts CNV inference to iST data, enabling spatial mapping of malignant clones and the tumor microenvironment, at single-cell resolution. Additionally, we assess how panel size and detection efficiency influence CNV inference.