Clustering and Markers Identification for ScRNA-Seq | Seurat Package Tutorial

Single Cell RNA-Sequencing have been a powerful tools for the understanding of the interactions in a group of cells that is close together. In the past the diluting effects have also been a problem in RNA-SEQ experiment whereby a smaller groups expressing a different groups of genes will get "diluted" by the surrounding cells. i.e. the guard cells in the leaves compared to the rest of the cells type. In the video I am adapting from a script developed by Satijalab on the first look at a single cell RNA-seq experiment. Including how the sample can be clustered into difference cell types using specific marker genes and how to make a great visualization on the analysis results. Original Script adapted from Satija Lab https://satijalab.org/seurat/articles... Script used in this video https://github.com/brandonyph/Introdu... Raw data https://s3-us-west-2.amazonaws.com/10... Useful Resources https://rdrr.io/bioc/DESeq2/man/varia... https://www.rdocumentation.org/packag... Chapters 1. Package Import 2:00 2. Data Import 2:30 3. Data QC and Inspection 4:20 4. Data Normalization 6:37 5. Data Clustering (PCA/UMAP) 9:10 6. Markers Identification 15:00 7. Putting all together 21:05 Email: [email protected] Website: https://www.liquidbrain.org/videos Patreon:   / liquidbrain