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.