Identification of PBMC-related cells of single cell RNA sequence data

Cell type identification is one of the main tasks of single cell RNA sequencing. This paper proposes an automatic identification of cell types based on random forest (AICTRF) method to identify cell types in single-cell sequencing data. This method uses the random forest classification model for training, and then predicts unknown cell types according to the trained model. A random forest classification model was trained on human peripheral blood mononuclear cells (PBMC) sequencing data set to predict the cell types of related subtypes of human PBMC B cells. The results show that the proposed method can help researchers automatically identify cell types in single-cell sequencing data.