An open multimodal spatial resource integrating same-tissue transcriptomics, proteomics, and histology

There are four zipped files shared here.

UnumLocalia

This contains the provided data to run UnumLocalia. This includes four cores: core01 (tumour HCC liver), core02 (non-tumour HCC liver), core03 (human tonsil), and core04 (human hepatocellular adenoma). Each core contains Xenium transcripts (including cell borders), COMET staining (ome.zarr file, marker thresholds), and H&E imaging (ome.zarr file). Alignment matrices are provided for the COMET and H&E images to align with Xenium data (which can be aligned and visualised using UnumLocalia).

Cell_quantifications

This contains single cells from each of the cores with quantified transcripts (Xenium) and protein (COMET) expression and COMET protein thresholds. These were generated in UnumLocalia, using the default Xenium cell masks. These data were used to generate the figures in the associated paper.

COMET_cell_masks

This contains cell masks for each of the cores generated using COMET data in QuPath (v0.6.0) using InstaSeg (model fluorescence_nuclei_and_cells-0.1.1). These masks can be read into UnumLocalia as an alternative cell mask.

COMET_ome_tiff

This contains ome.tiff files for each of the cores. This is an alternative format that can more easily be read into software like QuPath.

Citation

Please cite the bioRxiv paper associated with these data:

Duchini E, Tsao C, Madore J, Ashhurst T, De Almeida Silva J, Shin J, Gupta R, McCaughan G, Palendira U, Liu K, Ferguson A*, Marsh-Wakefield F*. An open multimodal spatial resource integrating same-tissue transcriptomics, proteomics, and histology. *Authors contributed equally. [DOI coming soon]