Nanopanel2 calls phased low-frequency variants in Nanopore panel sequencing data.


Journal

Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944

Informations de publication

Date de publication:
11 12 2021
Historique:
received: 21 01 2021
revised: 15 06 2021
accepted: 15 07 2021
medline: 13 4 2023
pubmed: 17 7 2021
entrez: 16 7 2021
Statut: ppublish

Résumé

Clinical decision making is increasingly guided by accurate and recurrent determination of presence and frequency of (somatic) variants and their haplotype through panel sequencing of disease-relevant genomic regions. Haplotype calling (phasing), however, is difficult and error prone unless variants are located on the same read which limits the ability of short-read sequencing to detect, e.g. co-occurrence of drug-resistance variants. Long-read panel sequencing enables direct phasing of amplicon variants besides having multiple other benefits, however, high error rates of current technologies prevented their applicability in the past. We have developed Nanopanel2, a variant caller for Nanopore panel sequencing data. Nanopanel2 works directly on base-called FAST5 files and uses allele probability distributions and several other filters to robustly separate true from false positive (FP) calls. It effectively calls SNVs and INDELs with variant allele frequencies as low as 1% and 5%, respectively, and produces only few low-frequency false-positive calls (∼1 FP call with VAF<5% per kb amplicon). Haplotype compositions are then determined by direct phasing. Nanopanel2 is the first somatic variant caller for Nanopore data, enabling accurate, fast (turnaround <48 h) and cheap (sequencing costs ∼10$/sample) diagnostic workflows. The data for this study have been deposited at zenodo.org under DOIs accession numbers 4110691 and 4110698. Nanopanel2 is open source and available at https://github.com/popitsch/nanopanel2. Supplementary data are available at Bioinformatics online.

Identifiants

pubmed: 34270680
pii: 6322985
doi: 10.1093/bioinformatics/btab526
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

4620-4625

Informations de copyright

© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Auteurs

Niko Popitsch (N)

Children's Cancer Research Institute, Vienna 1090, Austria.
Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna 1030, Austria.

Sandra Preuner (S)

Children's Cancer Research Institute, Vienna 1090, Austria.

Thomas Lion (T)

Children's Cancer Research Institute, Vienna 1090, Austria.
Department of Pediatrics, Medical University of Vienna, Vienna 1090, Austria.

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Classifications MeSH