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Evaluation of some aspects in supervised cell type identification for single-cell RNA-seq: classifier, feature selection, and reference construction.

Wenjing MaKenong SuHao Wu
Published in: Genome biology (2021)
Based on our analysis results, we provide guidelines for using supervised cell typing methods. We suggest combining all individuals from available datasets to construct the reference dataset and use multi-layer perceptron (MLP) as the classifier, along with F-test as the feature selection method. All the code used for our analysis is available on GitHub ( https://github.com/marvinquiet/RefConstruction_supervisedCelltyping ).
Keyphrases
  • single cell
  • rna seq
  • machine learning
  • high throughput
  • deep learning
  • stem cells
  • clinical practice
  • bone marrow