APARENT2 Training Data and Models

Processed training data for the APARENT2 model (measurements from the random MPRA and designed oligo pool originally published by Bogard et al., 2019; see https://doi.org/10.1016/j.cell.2019.04.046 for reference). This repository also contains the APARENT2 model file. For more information on the training procedure, see the <em>Genome Biology</em> article "Deciphering the impact of genetic variation on human polyadenylation using APARENT2" (https://genomebiology.biomedcentral.com/articles/10.1186/s13059-022-02799-4). Two versions of the model are available: (a) aparent_all_libs_resnet_no_clinvar_wt_ep_5.h5: The originally trained APARENT2 model.<br> (b) aparent_all_libs_resnet_no_clinvar_wt_ep_5_var_batch_size_inference_mode_no_drop.h5: Identical weights and predictions as model (a), but the normalization layers have been set to inference mode and the dropout layers have been removed (thus making it compatible with the scrambler pipeline).