scDA

scDA (Single Cell Discriminant Analysis) is a novel computational tool designed to address the challenges posed by analyzing large-scale single-cell RNA-sequencing (scRNA-seq) data. As scRNA-seq techniques unveil the phenotypic and molecular diversity within complex biological systems, they also introduce significant computational hurdles in accurately and efficiently characterizing diverse cell populations. scDA tackles these issues by leveraging a unique approach that identifies cell groups and discriminant metagenes by constructing a cell-by-cell representation graph. This methodology facilitates the determination of cell types and enhances the ability to annotate unlabeled cells within the data.

Topic

RNA-Seq;Genotype and phenotype;Cell biology;RNA;Transcriptomics

Detail

  • Operation: Essential dynamics;Gene expression profiling;Dimensionality reduction

  • Software interface: Command-line user interface

  • Language: MATLAB,C,C++,Python,Fortran

  • License: Not stated

  • Cost: Free of charge

  • Version name: -

  • Credit: National Natural Science Foundation of China, Strategic Priority Research Program of the Chinese Academy of Sciences, Shanghai Municipal Science and Technology Major Project, Huazhong Agricultural University Scientific and Technological Self-innovation Foundation.

  • Input: -

  • Output: -

  • Contact: Chuanchao Zhang chaozhangchuan@163.com ,Luonan Chen lnchen@sibs.ac.cn

  • Collection: -

  • Maturity: -

Publications

  • scDA: Single cell discriminant analysis for single-cell RNA sequencing data.
  • Shi Q, et al. scDA: Single cell discriminant analysis for single-cell RNA sequencing data. scDA: Single cell discriminant analysis for single-cell RNA sequencing data. 2021; 19:3234-3244. doi: 10.1016/j.csbj.2021.05.046
  • https://doi.org/10.1016/J.CSBJ.2021.05.046
  • PMID: 34141142
  • PMC: PMC8187165

Download and documentation

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