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Loan T. Nguyen

dblp:305/6047 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2021
0000-0002-7783-5466ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › sequence analysis › sequencing data analysis
read filtering
0.512021
Prowler: a novel trimming algorithm for Oxford Nanopore sequence data · Bioinform. 2021
Bioinformatics and computational biology
sequence analysis
0.512021
Prowler: a novel trimming algorithm for Oxford Nanopore sequence data · Bioinform. 2021

Methods — techniques the papers use, named apart from their topics

window-based trimming · 0.5
YearPublicationVenuePosition
2021 Prowler: a novel trimming algorithm for Oxford Nanopore sequence data
abstract
MOTIVATION: 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. RESULTS: Prowler was applied to mammalian and bacterial datasets, to assess its effect on alignment and assembly, respectively. Compared to data filtered with Nanofilt, alignments of data trimmed with Prowler had lower error rates and more mapped reads. Assemblies of Prowler trimmed data had a lower error rate than those filtered with Nanofilt; however, this came at some cost to assembly contiguity. AVAILABILITY AND IMPLEMENTATION: Prowler is implemented in Python and is available at https://github.com/ProwlerForNanopore/ProwlerTrimmer. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Simon Lee, Loan T. Nguyen, Ben J. Hayes, Elizabeth M. Ross
Bioinform.2