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bioRxiv · 10.1101/2021.05.09.443332

Prowler: A novel trimming algorithm for Oxford Nanopore sequence data

Lee, S.·Nguyen, L. T.·Hayes, B. J.·Ross, E. M.
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Abstract

MotivationQuality control (QC) tools are critical in DNA sequencing analysis because they increase the accuracy of sequence alignments and thus the reliability of results. Oxford Nanopore Technologies (ONT) QC is currently rudimentary, generally based on whole read average quality. This results in discarding reads that contain regions of high quality sequence. Here we propose Prowler, a multi-window approach inspired by algorithms used to QC short read data. Importantly, we retain the phase and read length information by optionally replacing trimmed sections with Ns. ResultsProwler was applied to mammalian and bacterial datasets, to assess effects on alignment and assembly respectively. Compared to Nanofilt, alignments of data QCed with Prowler had lower error rates and more mapped reads. Assemblies of Prowler QCed data had a lower error rate than Nanofilt QCed data however this came at some cost to assembly contiguity. Availability and implementationProwler is implemented in Python and is available at: https://github.com/ProwlerForNanopore/ProwlerTrimmer Contacte.ross@uq.edu.au Supplementary informationSupplementary data are available at Bioinformatics online.

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Lee, S., Nguyen, L. T., Hayes, B. J., Ross, E. M.. 2021-05-10. Prowler: A novel trimming algorithm for Oxford Nanopore sequence data. https://doi.org/10.1101/2021.05.09.443332

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