English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In light of the continuous transmission and evolution of SARS-CoV-2 coupledwith a significant decline in clinical testing, there is a pressing need forscalable, cost-effective, long-term, passive surveillance tools to effectivelymonitor viral variants circulating in the population. Wastewater genomicsurveillance of SARS-CoV-2 has arrived as an alternative to clinical genomicsurveillance, allowing to continuously monitor the prevalence of viral lineagesin communities of various size at a fraction of the time, cost, and logisticeffort and serving as an early warning system for emerging variants, criticalfor developed communities and especially for underserved ones. Importantly,lineage prevalence estimates obtained with this approach aren't distorted bybiases related to clinical testing accessibility and participation. However,the relative performance of bioinformatics methods used to measure relativelineage abundances from wastewater sequencing data is unknown, preventing boththe research community and public health authorities from making informeddecisions regarding computational tool selection. Here, we performcomprehensive benchmarking of 18 bioinformatics methods for estimating therelative abundance of SARS-CoV-2 (sub)lineages in wastewater by using data from36 in vitro mixtures of synthetic lineage and sublineage genomes. In addition,we use simulated data from 78 mixtures of lineages and sublineages co-occurringin the clinical setting with proportions mirroring their prevalence ratiosobserved in real data. Importantly, we investigate how the accuracy of theevaluated methods is impacted by the sequencing technology used, the associatederror rate, the read length, read depth, but also by the exposure of thesynthetic RNA mixtures to wastewater, with the goal of capturing the effectsinduced by the wastewater matrix, including RNA fragmentation and degradation.

A rigorous benchmarking of methods for SARS-CoV-2 lineage abundance estimation in wastewater