Dataset folders from "TISSUE: uncertainty-calibrated prediction of single-cell spatial transcriptomics improves downstream analyses". If using the processed data or TISSUE algorithm, please cite: https://doi.org/10.1101/2023.04.25.538326. The directory of datasets are compressed in tar gzip format. The top level contains folders with dataset names and within each of those folders, there are the relevant data files which include: - Spatial_count.txt --- a tab-delimited file containing spatial transcriptomics counts matrix - scRNA_count.txt --- a tab-delimited file containing RNAseq counts matrix - Locations.txt --- a tab-delimited file containing the (x,y) spatial coordinates of cells in the spatial transcriptomics data - Metadata.txt --- for some datasets, this is a comma-separated file containing the metadata table for the spatial transcriptomics data These files are formatted and organized to be read into AnnData objects using the native loading functions in the TISSUE package (https://github.com/sunericd/TISSUE). Some folders will also have additional accessory files such as gene lists corresponding to some experiments present in our manuscript and/or adjacency matrix objects. Also included are the two simulated spatial transcriptomics datasets that we generated using SRTsim. The SVZ folders contain our processed MERFISH spatial transcriptomics dataset on the adult mouse subventricular zone. Refer to the SVZFullFinal folder for the full dataset with TISSUE-informed cell labels. All other folders are processed data accessed from publicly available sources. The identity of numbered folders can be found in the Data Availability statement of the benchmarking paper from which they were retrieved: https://doi.org/10.1038/s41592-022-01480-9 "svz_merfish_data.zip" includes the raw MERFISH dataset on the adult mouse subventricular zone.