Transfer learning enables prediction of CYP2D6 haplotype function

This data here were used to train the models described in the manuscript "Transfer learning enables prediction of CYP2D6 haplotype function". The deep learning model described predicts metabolic function of <em>CYP2D6</em> star alleles. It uses two pretraining steps, first with simulated data, then with sequence data collected from liver microsomes, and finally using sequence data for <em>CYP2D6</em> star alleles. simulated_cyp2d6_diplotypes.tar.gz - This file contains sequence data and labels for simulated <em>CYP2D6 </em>data used in the first training step dalton_2019_cyp2d6_microsomes.txt - This file contains summary statistic data for liver microsome data used in the second pretraining step (originally from https://doi.org/10.1111/cts.12695) star_samples.vcf - This file contains sequence data for <em>CYP2D6 </em>star alleles derived from PharmVar (https://www.pharmvar.org/gene/CYP2D6) used in the final training step.