Sequencing-based measurements of genomes, epigenomes, transcriptomes, proteomes and other macromolecules can be obtained from more than a million single cells or nuclei per experiment in some cases, with multi-omic approaches enabling direct associations between different molecular layers. Although these methods enable data interpretation at scale, the spatial location of cells is lost when using single-cell or single-nucleus suspensions. To address this challenge, spatially resolved sequencing technologies capture macromolecules onto arrays of spatial barcodes, referred to as spots or pixels. Tissue sections are applied to these surfaces, capturing the macromolecule of interest and assigning a spatial coordinate. Because these methods impose an artificial structure onto tissues, they often capture a mixture of molecules from neighbouring cells. Moreover, they can miss information owing to gaps between capture areas. Consequently, new or adapted analysis tools for single-cell data are needed, and time-consuming bespoke approaches are often required to add additional measurement modalities.

The Slide-tags technology can be integrated with virtually any single-cell sequencing method, as demonstrated for droplet-based multi-omic assay for transposase-accessible chromatin with sequencing (ATAC-seq) and single-nucleus RNA sequencing on a metastatic melanoma sample.