Current tools for single-cell spatial omics still face barriers with regard to incomplete molecular profiling, tissue loss, and probe failure. Here, the authors use machine learning for the imputation of protein abundance in tissue-based cyclic immunofluorescence, showing that the spatial context can improve the accuracy of the imputation outputs.
- Raphael Kirchgaessner
- Cameron Watson
- Jeremy Goecks