SuperCT: a supervised-learning framework for enhanced characterization of single-cell transcriptomic profiles.

Journal: Nucleic acids research
PMID: 30799483

Abstract

Characterization of individual cell types is fundamental to the study of multicellular samples. Single-cell RNAseq techniques, which allow high-throughput expression profiling of individual cells, have significantly advanced our ability of this task. Currently, most of the scRNA-seq data analyses are commenced with unsupervised clustering. Clusters are often assigned to different cell types based on the enriched canonical markers. However, this process is inefficient and arbitrary. In this study, we present a technical framework of training the expandable supervised-classifier in order to reveal the single-cell identities as soon as the single-cell expression profile is input. Using multiple scRNA-seq datasets we demonstrate the superior accuracy, robustness, compatibility and expandability of this new solution compared to the traditional methods. We use two examples of the model upgrade to demonstrate how the projected evolution of the cell-type classifier is realized.

Authors

  • Peng Xie
    New Cornerstone Science Laboratory, SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, Jiangsu 210096, China.
  • Mingxuan Gao
    Xiamen University, Department of Chemical Biology, Xiamen, Fujian, China.
  • Chunming Wang
    National Engineering Research Center for Miniaturized Detection System, Northwest University, Xi'an, Shaanxi, China.
  • Jianfei Zhang
    College of Mathematics and Informatics, Fujian Normal University, Fuzhou 350117, China; Département d'Informatique, Université de Sherbrooke, Québec J1K 2R1, Canada. Electronic address: jianfei.zhang@usherbrooke.ca.
  • Pawan Noel
    Translational Genomics Research Institute, Molecular Medicine Division, Phoenix, AZ, USA.
  • Chaoyong Yang
    Xiamen University, State Key Lab of Physical Chemistry of Solid Surfaces, 482 Siming South,, Siming Qu, 361005, Xiamen, CHINA.
  • Daniel Von Hoff
    Translational Genomics Research Institute, Molecular Medicine Division, Phoenix, AZ, USA.
  • Haiyong Han
    Translational Genomics Research Institute, Molecular Medicine Division, Phoenix, AZ, USA.
  • Michael Q Zhang
    Department of Biological Sciences, Center for Systems Biology.
  • Wei Lin
    Department of Geriatric Rehabilitation, Jiangbin Hospital, Nanning, China.

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