Characterizing cell subsets using marker enrichment modeling - Diggins, Kirsten E; Greenplate, Allison R; Leelatian, Nalin; Wogsland, Cara E; Irish, Jonathan M (Nature methods, 2017)
Marker enrichment modeling (MEM) provides an objective metric for characterizing cell populations from high-content single-cell analysis. The MEM score outperforms standard metrics and provides a machine-readeable label for cell subsets. Learning cell identity from high-content single-cell data presently relies on human experts. We present marker enrichment modeling (MEM), an algorithm that objectively describes cells by quantifying contextual feature enrichment and reporting a human- and machine-readable text label. MEM outperforms traditional metrics in describing immune and cancer cell subsets from fluorescence and mass cytometry. MEM provides a quantitative language to communicate characteristics of new and established cytotypes observed in complex tissues.