Determining the spatial location from which a human tissue sample was extracted is important for analyses when tissue context matters. Traditional methods rely on textual annotations (e.g., organ or anatomical terms) and lack details on the size, location, and orientation of a tissue sample. The Human Reference Atlas API uses biomarker expression profile similarities to predict three-dimensional tissue locations, a critical improvement for atlas construction and essential for downstream applications like disease diagnostics and targeted treatments. The Tissue Origin Predictor is a no-code user interface that allows users to upload a cell type population and get a predicted spatial origin 3D volume (Börner et al. 2025). Predictions made with the Tissue Origin Predictor are at the anatomical structure level, not the organ level (Bueckle et al. 2025). In other words, predicted origins are identified to a more granular level than the organ, which is especially important given the diverse anatomy and varying cell type populations found within single organs.