DeepMEL2 GABPA#
The DeepMEL2 GABPA model is a topic classification model that is trained on the same data and with the same architecture as DeepMEL2.
On top of the 47 topics from DeepMEL2, this model includes a 48th class in which regions in input data were labeled as 1 if it overlaps with GABPA ChIP-seq peaks.
Details of the data and model can be found in the original publication.
Citation
Atak, Z.K., Taskiran, I.I. et al. Interpretation of allele-specific chromatin accessibility using cell state-aware deep learning. Genome Res. 31, 1082–1096 (2021). https://doi.org/10.1101/gr.260851.120
Usage#
1import crested
2import keras
3
4# download model
5model_path, output_names = crested.get_model("DeepMEL2_gabpa")
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)