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Rescuing Low Frequency Variants within Intra-Host Viral Populations directly from Oxford Nanopore sequencing data
Infectious disease monitoring on Oxford Nanopore Technologies (ONT) platforms offers rapid turnaround times and low cost, exemplified by well over a half of million ONT SARS-COV-2 datasets. Tracking low frequency intra-host variants has provided important insights with respect to elucidating within...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8437309/ https://www.ncbi.nlm.nih.gov/pubmed/34518837 http://dx.doi.org/10.1101/2021.09.03.458038 |
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author | Liu, Yunxi Kearney, Joshua Mahmoud, Medhat Kille, Bryce Sedlazeck, Fritz J. Treangen, Todd J. |
author_facet | Liu, Yunxi Kearney, Joshua Mahmoud, Medhat Kille, Bryce Sedlazeck, Fritz J. Treangen, Todd J. |
author_sort | Liu, Yunxi |
collection | PubMed |
description | Infectious disease monitoring on Oxford Nanopore Technologies (ONT) platforms offers rapid turnaround times and low cost, exemplified by well over a half of million ONT SARS-COV-2 datasets. Tracking low frequency intra-host variants has provided important insights with respect to elucidating within host viral population dynamics and transmission. However, given the higher error rate of ONT, accurate identification of intra-host variants with low allele frequencies remains an open challenge with no viable solutions available. In response to this need, we present Variabel, a novel approach and first method designed for rescuing low frequency intra-host variants from ONT data alone. We evaluated Variabel on both within patient and across patient paired Illumina and ONT datasets; our results show that Variabel can accurately identify low frequency variants below 0.5 allele frequency, outperforming existing state-of-the-art ONT variant callers for this task. Variabel is open-source and available for download at: www.gitlab.com/treangenlab/variabel. |
format | Online Article Text |
id | pubmed-8437309 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-84373092021-09-14 Rescuing Low Frequency Variants within Intra-Host Viral Populations directly from Oxford Nanopore sequencing data Liu, Yunxi Kearney, Joshua Mahmoud, Medhat Kille, Bryce Sedlazeck, Fritz J. Treangen, Todd J. bioRxiv Article Infectious disease monitoring on Oxford Nanopore Technologies (ONT) platforms offers rapid turnaround times and low cost, exemplified by well over a half of million ONT SARS-COV-2 datasets. Tracking low frequency intra-host variants has provided important insights with respect to elucidating within host viral population dynamics and transmission. However, given the higher error rate of ONT, accurate identification of intra-host variants with low allele frequencies remains an open challenge with no viable solutions available. In response to this need, we present Variabel, a novel approach and first method designed for rescuing low frequency intra-host variants from ONT data alone. We evaluated Variabel on both within patient and across patient paired Illumina and ONT datasets; our results show that Variabel can accurately identify low frequency variants below 0.5 allele frequency, outperforming existing state-of-the-art ONT variant callers for this task. Variabel is open-source and available for download at: www.gitlab.com/treangenlab/variabel. Cold Spring Harbor Laboratory 2021-09-06 /pmc/articles/PMC8437309/ /pubmed/34518837 http://dx.doi.org/10.1101/2021.09.03.458038 Text en https://creativecommons.org/licenses/by-nd/4.0/This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, and only so long as attribution is given to the creator. The license allows for commercial use. |
spellingShingle | Article Liu, Yunxi Kearney, Joshua Mahmoud, Medhat Kille, Bryce Sedlazeck, Fritz J. Treangen, Todd J. Rescuing Low Frequency Variants within Intra-Host Viral Populations directly from Oxford Nanopore sequencing data |
title | Rescuing Low Frequency Variants within Intra-Host Viral Populations directly from Oxford Nanopore sequencing data |
title_full | Rescuing Low Frequency Variants within Intra-Host Viral Populations directly from Oxford Nanopore sequencing data |
title_fullStr | Rescuing Low Frequency Variants within Intra-Host Viral Populations directly from Oxford Nanopore sequencing data |
title_full_unstemmed | Rescuing Low Frequency Variants within Intra-Host Viral Populations directly from Oxford Nanopore sequencing data |
title_short | Rescuing Low Frequency Variants within Intra-Host Viral Populations directly from Oxford Nanopore sequencing data |
title_sort | rescuing low frequency variants within intra-host viral populations directly from oxford nanopore sequencing data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8437309/ https://www.ncbi.nlm.nih.gov/pubmed/34518837 http://dx.doi.org/10.1101/2021.09.03.458038 |
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