title: Single cell proteomics in biomedicine: High-dimensional data acquisition, visualization, and analysis.
abstract: New insights on cellular heterogeneity in the last decade provoke the development of a variety of single cell omics tools at a lightning pace. The resultant high-dimensional single cell data generated by these tools require new theoretical approaches and analytical algorithms for effective visualization and interpretation. In this review, we briefly survey the state-of-the-art single cell proteomic tools with a particular focus on data acquisition and quantification, followed by an elaboration of a number of statistical and computational approaches developed to date for dissecting the high-dimensional single cell data. The underlying assumptions, unique features, and limitations of the analytical methods with the designated biological questions they seek to answer will be discussed. Particular attention will be given to those information theoretical approaches that are anchored in a set of first principles of physics and can yield detailed (and often surprising) predictions.
authors.affiliation: NanoSystems Biology Cancer Center, Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, USA.
authors.forename: Yapeng
authors.initials: Y
authors.lastname: Su
authors.affiliation: Key Laboratory of Systems Biomedicine (Ministry of Education), School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
authors.forename: Qihui
authors.initials: Q
authors.lastname: Shi
authors.affiliation: NanoSystems Biology Cancer Center, Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, USA.|Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California - Los Angeles, Los Angeles, CA, USA.
authors.forename: Wei
authors.initials: W
authors.lastname: Wei
mesh_terms: D000465:Algorithms; D000818:Animals; D001703:Biophysics / Q000379:methods; D019295:Computational Biology / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D040901:Proteomics / Q000379:methods* / Q000706:statistics & numerical data; D059010:Single-Cell Analysis / Q000379:methods* / Q000706:statistics & numerical data
keywords: Information theoretical approaches; Mass cytometry; Single cell barcode chip; Single cell data analysis; Single cell proteomics