Department of Molecular Biotechnology and Health Sciences, University of Torino, Torino, Italy.
Department of Computer Science, University of Torino, Torino, Italy.
Methods Mol Biol. 2021;2284:289-301. doi: 10.1007/978-1-0716-1307-8_16.
Single-cell RNAseq data can be generated using various technologies, spanning from isolation of cells by FACS sorting or droplet sequencing, to the use of frozen tissue sections retaining spatial information of cells in their morphological context. The analysis of single cell RNAseq data is mainly focused on the identification of cell subpopulations characterized by specific gene markers that can be used to purify the population of interest for further biological studies. This chapter describes the steps required for dataset clustering and markers detection using a droplet dataset and a spatial transcriptomics dataset.
单细胞 RNAseq 数据可以使用各种技术生成，包括通过 FACS 分选或液滴测序分离细胞，以及使用保留细胞形态学背景下空间信息的冷冻组织切片。单细胞 RNAseq 数据分析主要集中在鉴定具有特定基因标记的细胞亚群，这些标记可用于纯化感兴趣的细胞群体，以进行进一步的生物学研究。本章描述了使用液滴数据集和空间转录组学数据集进行数据集聚类和标记物检测所需的步骤。
