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.…
Verfasserangaben: | 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 |
Titel des übergeordneten Werks (Englisch): | Bioinformatics |
Untertitel (Englisch): | precise and scalable adaptive sampling for nanopore sequencing |
Verlag: | Oxford Univ. Press |
Verlagsort: | Oxford |
Publikationstyp: | Wissenschaftlicher Artikel |
Sprache: | Englisch |
Datum der Erstveröffentlichung: | 27.06.2022 |
Erscheinungsjahr: | 2022 |
Datum der Freischaltung: | 02.02.2024 |
Band: | 38 |
Ausgabe: | SUPPL 1 |
Seitenanzahl: | 8 |
Erste Seite: | 153 |
Letzte Seite: | 160 |
Fördernde Institution: | BMBF/German Center for Infection Research [TI 06.904-FP2019] |
Organisationseinheiten: | Digital Engineering Fakultät / Hasso-Plattner-Institut für Digital Engineering GmbH |
DDC-Klassifikation: | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik |
Peer Review: | Referiert |
Publikationsweg: | Open Access / Hybrid Open-Access |
DOAJ gelistet | |
Lizenz (Deutsch): | CC-BY - Namensnennung 4.0 International |