DeepMEL2 GABPA

Contents

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)