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Network model to predict gene expression and cell properties from masked-out scRNA data

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DiseaseNeuroGenomics/perceiver

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perceiver

Network model to predict gene expression and cell properties from masked-out scRNA data

Network model based off of "A single-cell gene expression language model" https://arxiv.org/abs/2210.14330

which in turn is based on the Perceiver IO architecture https://arxiv.org/abs/2107.14795

Creating the train and test set

Run create_dataset.py - must modify source_path and target_path in file Source data must be taken from /sc/arion/projects/psychAD/NPS-AD/.../*.h5ad Creates a numpy memmap data structure for the epxression data, and a pkl file for the cell properties and other metadata

Training the model

Run train.py Network and training configs are found in config.py

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Network model to predict gene expression and cell properties from masked-out scRNA data

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