(MEMPHIS, Tenn. – December 3, 2025) Spatial transcriptomics provides a unique perspective on the genes that cells express and where those cells are located. However, the rapid growth of the technology has come at the cost of standardization and consistency. To address this, the multi-institutional Spatial Touchstone project collected publicly available spatial transcriptomics imaging data and combined it with newly generated, curated datasets from six tissue types. The resulting repository, standardized protocols and open-source software package are available online, allowing researchers to control the quality of their own datasets and reliably compare them across institutions. The undertaking was published today in Nature Biotechnology.
The unmatched detail of spatial transcriptomics has allowed researchers to understand cellular microenvironments such as tumors and developing brains like never before. However, each revelation requires a serious investment in time, money and resources, so ensuring a return on investment is vital.
Co-first and co-corresponding author Jasmine Plummer, PhD , St. Jude Center for Spatial Omics director and Department of Developmental Neurobiology member, found that the spatial transcriptomics field needed more resources to maximize return. "The project started because I was frustrated with the field lacking quality metrics," Plummer said. "Other technologies have established baseline expectations using set cell lines to tell if variation is due to the sample, machine or technician."
A framework for robust spatial data analysis
To fill this need within the spatial transcriptomics community and improve access to quality control, Plummer and a global coalition of like-minded researchers formed the Spatial Touchstone project. "We established statistical methods and metrics, which are important because, currently, images are often analyzed without quality control," Plummer said. "For example, how many transcripts should be in a cell? What's normal for a prostate or brain?"
The resulting collated dataset included samples collected from breast, prostate, colon, appendix, ileum and pancreas tissues spanning both healthy and diseased tissues across two platforms and cross-institute replicates. It provides critical insight into how these tissues should look in a sample. The dataset is paired with a software tool, Spatial QM, which provides metrics on how these samples performed on different spatial transcriptomics platforms.
An accompanying user-friendly application called the Spatial Touchstone Portal (STP) will allow users to screen their own preliminary samples against the dataset and decide if they should move forward with an experiment. "The portal is designed to view metrics by tissue so you can see how samples perform," Plummer explained. "Users can understand if their samples pass or fail the quality check, which is important because analyzing a terabyte of data is a lot of work."
The final components are the Spatial Touchstone Standard Operating Procedures (STSOP), which democratize a range of protocols from tissue preparation to data acquisition and embed consistency and reproducibility within the field. "Every individual lab is different, but we wanted a set of protocols where people can feel confident in their methods and the expected outcomes," Plummer said. "We operate many samples and are leaders in the field, so if your sample keeps failing, consider using our protocols."
