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Prowler: a novel trimming algorithm for Oxford Nanopore sequence data.

Simon Lee1, Loan T Nguyen1, Ben J Hayes1

  • 1Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD 4069, Australia.

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This summary is machine-generated.

Prowler, a new DNA sequencing tool, improves Oxford Nanopore Technologies (ONT) data analysis by using a window-based trimming approach. This method enhances sequence alignment accuracy and reliability for better results.

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Area of Science:

  • Genomics
  • Bioinformatics

Background:

  • DNA sequencing analysis relies on accurate alignments for reliable results.
  • Current Oxford Nanopore Technologies (ONT) trimming tools are basic, often discarding high-quality sequence regions.
  • A need exists for advanced trimming tools to optimize ONT data quality.

Purpose of the Study:

  • Introduce Prowler, a novel window-based trimming tool for ONT data.
  • Evaluate Prowler's performance against existing methods like Nanofilt.
  • Improve the accuracy and reliability of DNA sequence alignments and assemblies.

Main Methods:

  • Developed Prowler using a window-based approach, inspired by short-read trimming algorithms.
  • Implemented optional replacement of trimmed sections with 'N's to preserve phase and read length information.
  • Applied Prowler to mammalian and bacterial datasets for alignment and assembly assessments.

Main Results:

  • Prowler-trimmed data showed lower error rates and higher mapped read counts in alignments compared to Nanofilt.
  • Assemblies from Prowler-trimmed data exhibited reduced error rates.
  • A slight decrease in assembly contiguity was observed with Prowler trimming.

Conclusions:

  • Prowler offers a significant improvement over basic ONT filtering methods.
  • The window-based approach enhances alignment accuracy and assembly quality.
  • Prowler is a valuable tool for optimizing Oxford Nanopore Technologies data analysis.