Identifying centromeric satellites with dna-brnn

Summary: Human alpha satellite and satellite 2/3 contribute to several percent of the human genome. However, identifying these sequences with traditional algorithms is computationally intensive. Here we develop dna-brnn, a recurrent neural network to learn the sequences of the two classes of centromeric repeats. It achieves high similarity to RepeatMasker and is tens of times faster. Dna-brnn explores a novel application of deep learning and may accelerate the study of the evolution of the two repeat classes. Availability and implementation: https://github.com/lh3/dna-nn Contact: hli@jimmy.harvard.edu