Characterizing cell subsets using marker enrichment modeling.

Diggins KE, Greenplate AR, Leelatian N, Wogsland CE, Irish JM
Nat Methods. 2017 14 (3): 275-278

PMID: 28135256 · PMCID: PMC5330853 · DOI:10.1038/nmeth.4149

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.

MeSH Terms (9)

Algorithms Biomarkers Brain Neoplasms Computational Biology Flow Cytometry Glioblastoma Humans Single-Cell Analysis T-Lymphocytes

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