RODAN: a fully convolutional architecture for basecalling nanopore RNA sequencing data

BACKGROUND: Despite recent progress in basecalling of Oxford nanopore DNA sequencing data, its wide adoption is still being hampered by its relatively low accuracy compared to short read technologies. Furthermore, very little of the recent research was focused on basecalling of RNA data, which has d...

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Detalles Bibliográficos
Autores principales: Neumann, Don, Reddy, Anireddy S. N., Ben-Hur, Asa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9020074/
https://www.ncbi.nlm.nih.gov/pubmed/35443610
http://dx.doi.org/10.1186/s12859-022-04686-y
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author Neumann, Don
Reddy, Anireddy S. N.
Ben-Hur, Asa
author_facet Neumann, Don
Reddy, Anireddy S. N.
Ben-Hur, Asa
author_sort Neumann, Don
collection PubMed
description BACKGROUND: Despite recent progress in basecalling of Oxford nanopore DNA sequencing data, its wide adoption is still being hampered by its relatively low accuracy compared to short read technologies. Furthermore, very little of the recent research was focused on basecalling of RNA data, which has different characteristics than its DNA counterpart. RESULTS: We fill this gap by benchmarking a fully convolutional deep learning basecalling architecture with improved performance compared to Oxford nanopore’s RNA basecallers. AVAILABILITY: The source code for our basecaller is available at: https://github.com/biodlab/RODAN. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-022-04686-y.
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spelling pubmed-90200742022-04-21 RODAN: a fully convolutional architecture for basecalling nanopore RNA sequencing data Neumann, Don Reddy, Anireddy S. N. Ben-Hur, Asa BMC Bioinformatics Research BACKGROUND: Despite recent progress in basecalling of Oxford nanopore DNA sequencing data, its wide adoption is still being hampered by its relatively low accuracy compared to short read technologies. Furthermore, very little of the recent research was focused on basecalling of RNA data, which has different characteristics than its DNA counterpart. RESULTS: We fill this gap by benchmarking a fully convolutional deep learning basecalling architecture with improved performance compared to Oxford nanopore’s RNA basecallers. AVAILABILITY: The source code for our basecaller is available at: https://github.com/biodlab/RODAN. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-022-04686-y. BioMed Central 2022-04-20 /pmc/articles/PMC9020074/ /pubmed/35443610 http://dx.doi.org/10.1186/s12859-022-04686-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visithttp://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Neumann, Don
Reddy, Anireddy S. N.
Ben-Hur, Asa
RODAN: a fully convolutional architecture for basecalling nanopore RNA sequencing data
title RODAN: a fully convolutional architecture for basecalling nanopore RNA sequencing data
title_full RODAN: a fully convolutional architecture for basecalling nanopore RNA sequencing data
title_fullStr RODAN: a fully convolutional architecture for basecalling nanopore RNA sequencing data
title_full_unstemmed RODAN: a fully convolutional architecture for basecalling nanopore RNA sequencing data
title_short RODAN: a fully convolutional architecture for basecalling nanopore RNA sequencing data
title_sort rodan: a fully convolutional architecture for basecalling nanopore rna sequencing data
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9020074/
https://www.ncbi.nlm.nih.gov/pubmed/35443610
http://dx.doi.org/10.1186/s12859-022-04686-y
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