VirPool: model-based estimation of SARS-CoV-2 variant proportions in wastewater samples
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Published:2022-12-19
Issue:1
Volume:23
Page:
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ISSN:1471-2105
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Container-title:BMC Bioinformatics
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language:en
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Short-container-title:BMC Bioinformatics
Author:
Gafurov Askar,Baláž Andrej,Amman Fabian,Boršová Kristína,Čabanová Viktória,Klempa Boris,Bergthaler Andreas,Vinař Tomáš,Brejová Broňa
Abstract
Abstract
Background
The genomes of SARS-CoV-2 are classified into variants, some of which are monitored as variants of concern (e.g. the Delta variant B.1.617.2 or Omicron variant B.1.1.529). Proportions of these variants circulating in a human population are typically estimated by large-scale sequencing of individual patient samples. Sequencing a mixture of SARS-CoV-2 RNA molecules from wastewater provides a cost-effective alternative, but requires methods for estimating variant proportions in a mixed sample.
Results
We propose a new method based on a probabilistic model of sequencing reads, capturing sequence diversity present within individual variants, as well as sequencing errors. The algorithm is implemented in an open source Python program called VirPool. We evaluate the accuracy of VirPool on several simulated and real sequencing data sets from both Illumina and nanopore sequencing platforms, including wastewater samples from Austria and France monitoring the onset of the Alpha variant.
Conclusions
VirPool is a versatile tool for wastewater and other mixed-sample analysis that can handle both short- and long-read sequencing data. Our approach does not require pre-selection of characteristic mutations for variant profiles, it is able to use the entire length of reads instead of just the most informative positions, and can also capture haplotype dependencies within a single read.
Funder
Agentúra na Podporu Výskumu a Vývoja Operačný program Integrovaná infraštruktúra Horizon 2020 Framework Programme Vedecká Grantová Agentúra MŠVVaŠ SR a SAV
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Structural Biology
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