Please follow the instructions to install Jupyter Notebook. You can use walkthrough examples to start.
1) Run cell ranger (advanced user) from python notebook to generate counts data: Run cell ranger.
2) Analyze using counts matrix (10X Genomic V3 Use), and load results into single cell explorer database (MongoDB): PBMC10k example for Python Notebook user.
The example demonstrated -- the analysis of 10X RNAseq using scanpy module -- Need of parameter optimization for leiden algorhism to find right cell clusters -- UMAP or t-SNE can be used by experimental scientists to annotate cells from their perspectives or goals
3) R user: Import counts table and tsne/umap coordinate from Seurat object or loom files: Import Data.
The example demonstrated -- extract results from Seurat object to single cell explorer -- Loom files support
4) Retrieve annoated cells using API and identify differentially expressed genes: DEG analysis (using API).
The example demonstrated -- use http API from application url to retrieve cell types and normalized expression matrix from single cell explorer database -- find differentially expressed genes