Fig. 1

Schematic representation of the sc2marker framework: The input is a clustered single-cell RNA-seq data set and a list of antibodies for the selected application; i.e., flow cytometry or imaging. For every potential marker and cell type, sc2marker finds an optimal threshold \(\alpha\) (or margin) with maximal distances to true positives (TP) and true negatives (TN) and low distances to false positives (FP) and false negatives (FN). The threshold score is used to rank markers for each cell type