单细胞RNA序列数据的PBMC相关细胞的识别

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

细胞类型鉴定是单细胞RNA测序的主要任务之一.针对整个问题,提出基于随机森林的细胞类型自动识别(automatic identification of cell type based on random forest,AICTRF)方法来识别单细胞测序数据中的细胞类型,该方法使用随机森林分类模型进行训练,根据训练的模型进而预测未知的细胞类型.在人类外周血单核细胞(PBMC)测序数据集上训练了随机森林分类模型,利用该模型预测了人类PBMC中B细胞的相关亚型细胞类型.实验结果表明,该方法可以帮助相关研究人员快速而有效地自动识别单细胞测序数据中的细胞类型.

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.