Firstly, we suggest to build a new virtual environment through Anaconda:
conda create -n FEGFS python=3.7
Create and activate the virtual environment environment FEGFS:
conda activate FEGFS
| package | version |
|---|---|
| pandas | 0.25.1 |
| numpy | 1.16.5 |
| scikit-learn | 0.21.3 |
| matplotlib | 3.3.1 |
All functions of FEGFS can be found in the script folder FEGFS.py is running:
python ./script/FEGFS.py -d <data_name> -c <num_clusters> -n <retention_ratio> -i <GO_Term_path> -e <expression_matrix_path> -o <outputpath> -l <label_path>
Run FEGFS as an example in script:
python ./script/FEGFS.py -d test -c 5 -n 0.4 -i ./example/GO_Term.xlsx -e ./example/test_count_matrix.csv -o ./example/Term_matrix -l ./example/test_label.csv
Here we take Pollen as an example:
python ./script/FEGFS.py -d pollen -c 11 -n 0.4 -i ./pollen/pollen_GO_Term.xlsx -e ./pollen/pollen_count_matrix.csv -o ./pollen/pollen_Term_matrix -l ./pollen/pollen_label.csv