DeepMouseBrain2#
The DeepMouseBrain2 model is a topic classification model, fine-tuned with differential accessible regions (DARs) to make cell type level predictions for cell types in the mouse neocortex, striatum and hippocampus. The dataset was obtained from Li et al., 2021 (Nature).
After pretraining on topics, obtained through pycistopic, DARs were calculated per cell type and used as cell type representation. These sets of regions were then used as input to the model, where 500bp one-hot encoded DNA sequences were used to predict the cell type(s) to which the regions belong.
The model is a CNN multiclass classifier which uses the deeptopic_cnn()
architecture.
Details of the data and the model can be found in the original publication.
Citation
Hecker, N., Kempynck, N. et al. Enhancer-driven cell type comparison reveals similarities between the mammalian and bird pallium. bioRxiv (2024). https://doi.org/10.1101/2024.04.17.589795
Usage#
1import crested
2import keras
3
4# download model
5model_path, output_names = crested.get_model("DeepMouseBrain2")
6
7# load model
8model = keras.models.load_model(model_path)
9
10# make predictions
11sequence = "A" * 500
12predictions = crested.tl.predict(sequence, model)
13print(predictions.shape)