Computational Biology
@ Comenius University in Bratislava

Askar Gafurov, Andrej Balaz, Fabian Amman, Kristina Borsova, Viktoria Cabanova, Boris Klempa, Andreas Bergthaler, Tomas Vinar, Brona Brejova. VirPool: Model-Based Estimation of SARS-CoV-2 Variant Proportions in Wastewater Samples. Technical Report 2022.06.21.22276717, medRxiv, 2022.

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Download from publisher: https://doi.org/10.1101/2022.06.21.22276717

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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 in a 
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 evaluated 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 alpha and delta variants.

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.

Availability VirPool is an open source software available at https://github.com/fmfi-compbio/virpool.