Single Cell data analysis tutorial on PBMC dataset using scanpy - Part2

In this video, we will go through standard steps to analyze a single-cell RNA sequencing dataset (PBMC) from 10X Genomics using the #scanpy package.
Jupyter notebook is available at: github.com/ram...
We cover the following sections:
1) Clustering using graph based clustering methods such as Leiden algorithm.
2) Gene expression analysis such as identifying differentially expressed genes/marker genes for each cluster
3) Cluster annotation (Cell type annotation)
To get in touch:
Twitter: / prakki_rama
Github: github.com/ram...
LinkedIn: / prakki-sai-rama-sridat...
#bioinformatics #scanpy #python #singlecell #genomics #beginners #anndata

[@DavidKaplanProgramming]

I have two datasets (one control and one cancer data) with similar vars and observations. Should I combine them together using scanpy concatenate and then normalise? or should I do the normalisation before?

[@asearchforsolutions]

Sorry, I missed this comment. Better to combine and process, in that way all filters are applied on both control and disease and helps visualize both datasets in the latent space. You may have to batch correct by donors if you have multiple donors.