scRNASeq analysis
Project description
SCanno Tutorial
1. Requirements:
- Python (v3.8.2)
- Scanpy (v1.81)
- Pandas (V1.3.4)
- Scikit_learn (v1.0.1)
- Tensorflow (v2.6.0)
2. Install
pip install scanno
3. Prepare Input Files
- Normalized (log1p) datasets in h5ad format (usually preprocessed using Scanpy)
- Marker gene information in csv format (the example file could be found in the example folder), which contains three columns:
- "cell": This column contains expected cell names.
- "marker": This column contains known marker genes for the given cell type. If there are more than one marker genes, insert "," between each gene symbol. Recommend using two markers for each cell type.
- "blocklist": This column contains the genes that used as markers for other cell types, but may also expressed in the given cell type.
4. Annotation
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