Serun singlecell data analysis notebook
Seurat - Guided Clustering Tutorial of 2,700 PBMCs
Downloading data from 10X Genomics
Setup the Seurat Object
QC and selecting cells for further analysis
Normalizing the data
Identification of highly variable features (feature selection)
Scaling the data
Perform linear dimensional reduction
Determine the ‘dimensionality’ of the dataset
Cluster the cells
Run non-linear dimensional reduction (UMAP/tSNE)
Finding differentially expressed features (cluster biomarkers)
Assigning cell type identity to clusters
Serun singlecell data analysis notebook
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