singleCellNet

SingleCellNet is a computational tool to classify single-cell RNA-seq data by comparing query cells to reference single-cell RNA-seq datasets. The tool addresses the limitations of traditional methods, which rely on searching for cell-type specific gene combinations and do not quantitatively leverage information from other single-cell RNA-seq studies. SingleCellNet outperforms other methods in terms of sensitivity and specificity, and it can classify cells across different platforms and species.

Topic

RNA-Seq

Detail

  • Operation: RNA-Seq quantification

  • Software interface: -

  • Language: R

  • License: MIT License

  • Cost: Free of charge with restrictions

  • Version name: v0.4.1

  • Credit: The National Institutes of Health, the Biochemistry, Cellular, and Molecular Biology Program training grant.

  • Input: -

  • Output: -

  • Contact: Patrick Cahan patrick.cahan@jhmi.edu

  • Collection: -

  • Maturity: -

Publications

  • SingleCellNet: A Computational Tool to Classify Single Cell RNA-Seq Data Across Platforms and Across Species.
  • Tan Y and Cahan P. SingleCellNet: A Computational Tool to Classify Single Cell RNA-Seq Data Across Platforms and Across Species. SingleCellNet: A Computational Tool to Classify Single Cell RNA-Seq Data Across Platforms and Across Species. 2019; 9:207-213.e2. doi: 10.1016/j.cels.2019.06.004
  • https://doi.org/10.1016/j.cels.2019.06.004
  • PMID: 31377170
  • PMC: PMC6715530

Download and documentation

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