Regensburg Germany

1 Introduction Radiotherapy is a well-established treatment for patients with prostate cancer [1]. Advances in radiotherapy techniques, such as intensity-modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT), have significantly reduced toxicity compared to three-dimensional radiotherapy by enhancing dose conformity and sparing normal tissues [2].

Bulk RNA expression data is widely accessible, whereas single-cell data is relatively scarce in comparison. However, single-cell data offers profound insights into the cellular composition of tissues and cell type-specific gene regulation, both of which remain hidden in bulk expression analysis. Here, we present tissueResolver, an algorithm designed to extract single-cell information from bulk data, enabling us to attribute expression changes to individual cell types.