A flexible deep neural network framework for predicting the transcript distribution of the spatial transcriptomics
- python 3.9.12
- pytorch 1.12.1
- numpy 1.21.6
- pandas 1.4.4
- scikit-learn 1.0.2
- tqdm
- logzero
- ruamel.yaml
- click
- torchvision
The data used in our research can be downloaded from https://zenodo.org/record/8063157
- Unzip data and make dir for saved_model and results.
tar -zxvf data.tar.gz
mkdir result
mkdir saved_model
- Run preprocess.py to generate positive samples between spatial transcriptomics.
python preprocess.py -c ./configure/osmFISH_Zeisel.yaml
- Run main.py to train and predict the transcript distribution of the spatial transcriptomics.
python main.py -c ./configure/osmFISH_Zeisel.yaml