@article {Boemo2020.11.04.368225, author = {Michael A. Boemo}, title = {DNAscent v2: Detecting Replication Forks in Nanopore Sequencing Data with Deep Learning}, elocation-id = {2020.11.04.368225}, year = {2020}, doi = {10.1101/2020.11.04.368225}, publisher = {Cold Spring Harbor Laboratory}, abstract = {The detection of base analogues in Oxford Nanopore Technologies (ONT) sequencing reads has become a promising new method for the high-throughput measurement of DNA replication dynamics with single-molecule resolution. This paper introduces DNAscent v2, software that uses a residual neural network to achieve fast, accurate detection of the thymidine analogue BrdU with single-base resolution. DNAscent v2 comes equipped with an autoencoder that detects replication forks, origins, and termination sites in ONT sequencing reads from both synchronous and asynchronous cell populations, outcompeting previous versions and other tools across different experimental protocols. DNAscent v2 is open-source and available at https://github.com/MBoemo/DNAscent.Competing Interest StatementThe authors have declared no competing interest.}, URL = {https://www.biorxiv.org/content/early/2020/11/05/2020.11.04.368225}, eprint = {https://www.biorxiv.org/content/early/2020/11/05/2020.11.04.368225.full.pdf}, journal = {bioRxiv} }