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Basecalling Using Joint Raw and Event Nanopore Data Sequence-to-Sequence Processing.

Adam Napieralski1, Robert Nowak1

  • 1Institute of Computer Science, Faculty of Electronics and Information Technology, Warsaw University of Technology, 00-665 Warsaw, Poland.

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|March 26, 2022
PubMed
Summary
This summary is machine-generated.

We developed Ravvent, a novel DNA basecalling tool that combines raw and event data for improved accuracy. This approach surpasses existing methods, enhancing Oxford Nanopore Technologies sequencing data analysis.

Keywords:
attentionbasecallingbioinformaticsencoder decoderjoint processingmachine learningnanoporeneural networksequence-to-sequence

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Third-generation DNA sequencing, such as Oxford Nanopore Technologies (ONT), generates electrical current data.
  • Basecalling, the process of translating electrical signals into nucleotide sequences, remains a challenge with accuracy limitations.
  • Current basecalling methods primarily use raw electrical signal data or preprocessed event data.

Purpose of the Study:

  • To develop a novel basecalling method that improves accuracy by jointly processing both raw and event data from ONT sequencers.
  • To evaluate the performance of the proposed method against existing basecalling techniques.

Main Methods:

  • A novel basecaller, Ravvent, was developed using a recurrent neural network encoder-decoder architecture.
  • The model incorporates twin encoders and an attention mechanism for joint processing of raw and event data.
  • The approach defines basecalling as a sequence-to-sequence translation task.

Main Results:

  • Joint processing of raw and event data significantly improved basecalling accuracy compared to using either data type alone.
  • The proposed method demonstrated superior performance over the existing ONT basecaller, Guppy.
  • Numerical experiments on simulated and real datasets validated the effectiveness of the joint processing approach.

Conclusions:

  • Combining raw and event data offers a more accurate approach to DNA basecalling with Oxford Nanopore Technologies sequencing.
  • The Ravvent application provides a freely available, accurate solution for basecalling, advancing genomic data analysis.
  • This work highlights the potential of hybrid data processing strategies in improving nanopore sequencing accuracy.