The analysis of scRNA-seq data can be divided into two steps:
- generated a count matrix for all the genes and all the cells of one individual
- data analysis based on this count matrix (imputation, clustering, differential expression)
Also, we will discuss techniques that generate the scRNA-data, such as single-cell isolation and library preparation. For the comparison of 6 popular techs, please see Ziegenhain et al. (2017)
This documents will use publicly available datasets PBMCs
, around 68k peripheral blood mononuclear cells.
For the left panel, we will use Cell Ranger to process scRNA data from 10x Genomics. Then, we will use Seurat R package to process the data analysis.