SquiggleNet: real-time, direct classification of nanopore signals

We present SquiggleNet, the first deep-learning model that can classify nanopore reads directly from their electrical signals. SquiggleNet operates faster than DNA passes through the pore, allowing real-time classification and read ejection. Using 1 s of sequencing data, the classifier achieves sign...

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Detalles Bibliográficos
Autores principales: Bao, Yuwei, Wadden, Jack, Erb-Downward, John R., Ranjan, Piyush, Zhou, Weichen, McDonald, Torrin L., Mills, Ryan E., Boyle, Alan P., Dickson, Robert P., Blaauw, David, Welch, Joshua D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Method
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8548853/
https://www.ncbi.nlm.nih.gov/pubmed/34706748
http://dx.doi.org/10.1186/s13059-021-02511-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8548853/
https://www.ncbi.nlm.nih.gov/pubmed/34706748
http://dx.doi.org/10.1186/s13059-021-02511-y

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