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ReadBouncer

  • Motivation: Nanopore sequencers allow targeted sequencing of interesting nucleotide sequences by rejecting other sequences from individual pores. This feature facilitates the enrichment of low-abundant sequences by depleting overrepresented ones in-silico. Existing tools for adaptive sampling either apply signal alignment, which cannot handle human-sized reference sequences, or apply read mapping in sequence space relying on fast graphical processing units (GPU) base callers for real-time read rejection. Using nanopore long-read mapping tools is also not optimal when mapping shorter reads as usually analyzed in adaptive sampling applications. Results: Here, we present a new approach for nanopore adaptive sampling that combines fast CPU and GPU base calling with read classification based on Interleaved Bloom Filters. ReadBouncer improves the potential enrichment of low abundance sequences by its high read classification sensitivity and specificity, outperforming existing tools in the field. It robustly removes even readsMotivation: Nanopore sequencers allow targeted sequencing of interesting nucleotide sequences by rejecting other sequences from individual pores. This feature facilitates the enrichment of low-abundant sequences by depleting overrepresented ones in-silico. Existing tools for adaptive sampling either apply signal alignment, which cannot handle human-sized reference sequences, or apply read mapping in sequence space relying on fast graphical processing units (GPU) base callers for real-time read rejection. Using nanopore long-read mapping tools is also not optimal when mapping shorter reads as usually analyzed in adaptive sampling applications. Results: Here, we present a new approach for nanopore adaptive sampling that combines fast CPU and GPU base calling with read classification based on Interleaved Bloom Filters. ReadBouncer improves the potential enrichment of low abundance sequences by its high read classification sensitivity and specificity, outperforming existing tools in the field. It robustly removes even reads belonging to large reference sequences while running on commodity hardware without GPUs, making adaptive sampling accessible for in-field researchers. Readbouncer also provides a user-friendly interface and installer files for end-users without a bioinformatics background.show moreshow less

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Metadaten
Author details:Jens-Uwe UlrichORCiD, Ahmad Lutfi, Kilian Rutzen, Bernhard Y. RenardORCiDGND
DOI:https://doi.org/10.1093/bioinformatics/btac223
ISSN:1367-4803
ISSN:1460-2059
Pubmed ID:https://pubmed.ncbi.nlm.nih.gov/35758774
Title of parent work (English):Bioinformatics
Subtitle (English):precise and scalable adaptive sampling for nanopore sequencing
Publisher:Oxford Univ. Press
Place of publishing:Oxford
Publication type:Article
Language:English
Date of first publication:2022/06/27
Publication year:2022
Release date:2024/02/02
Volume:38
Issue:SUPPL 1
Number of pages:8
First page:153
Last Page:160
Funding institution:BMBF/German Center for Infection Research [TI 06.904-FP2019]
Organizational units:Digital Engineering Fakultät / Hasso-Plattner-Institut für Digital Engineering GmbH
DDC classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Peer review:Referiert
Publishing method:Open Access / Hybrid Open-Access
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License (German):License LogoCC-BY - Namensnennung 4.0 International
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