This is a comprehensive introduction into single-cell analysis in python. I recreate the main single cell analyses from a recent Nature publication. I explain the basics of single-cell sequencing analysis and also introduce more advanced topics. I cover doublet removal, preprocessing, integration, clustering, cell identification, differential expression, gene-set enrichment, non-parametric statistical testing, single-cell gene signature scoring, plotting, and more. This tutorial is suitable for both advance and new single-cell users. I use the scanpy and SCVI packages heavily.
Notebook:
https://github.com/mousepixels/sanbomics_scripts/blob/main/single_cell_analysis_complete_class.ipynb
Reference:
https://www.nature.com/articles/s41586-021-03569-1
0:00 intro
1:18 data
6:35 doublet removal
13:03 preprocessing
23:12 Clustering
27:42 Integration
39:56 label cell types
58:28 Analysis