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Prowler: a novel trimming algorithm for Oxford Nanopore sequence data
Author(s) -
Simon Lee,
Loan Nguyen,
Ben J. Hayes,
Elizabeth M. Ross
Publication year - 2021
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btab630
Subject(s) - trimming , algorithm , computer science , python (programming language) , nanopore sequencing , sequence assembly , trim , sequence (biology) , data mining , dna sequencing , biology , programming language , dna , biochemistry , gene expression , transcriptome , gene , genetics , operating system
Trimming and filtering tools are useful in DNA sequencing analysis because they increase the accuracy of sequence alignments and thus the reliability of results. Oxford nanopore technologies (ONT) trimming and filtering tools are currently rudimentary, generally only filtering reads based on whole read average quality. This results in discarding reads that contain regions of high-quality sequence. Here, we propose Prowler, a trimmer that uses a window-based approach inspired by algorithms used to trim short read data. Importantly, we retain the phase and read length information by optionally replacing trimmed sections with Ns.

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