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ZENODO
Other literature type . 2021
License: CC BY
Data sources: ZENODO
ZENODO
Other ORP type . 2021
License: CC BY
Data sources: Datacite
ZENODO
Other ORP type . 2021
License: CC BY
Data sources: Datacite
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Guidance document for WGS-Benchmarking

Authors: Sayeb, Maroua;

Guidance document for WGS-Benchmarking

Abstract

Whole genome sequencing (WGS) is increasingly used in diagnostics and surveillance of pathogenic microorganisms. Common applications for WGS is to use the data for the identification of pathogenic bacteria, antimicrobial resistance (AMR), virulence gene detection and during outbreak investigations. This guidance document presents how to benchmark the different WGS steps. A checklist was drafted for bacterial genome analysis using WGS technology that sets standards for the analytical wet lab (bench) process and bioinformatics analyses, also called "dry lab (bench)". In other words, bacterial WGS includes 2 steps: Analytical wet lab analyses; Bioinformatics analyses of reads obtained from sequencing. The wet bench component generally includes any or all of the following steps: handling of isolates, DNA extraction, DNA fragmentation, barcoding (molecular indexing) of DNA fragments, enrichment of gene targets within certain panels, adapter ligation, amplification, library preparation, flow cell loading, and generation of sequence reads. Generation of reads is almost entirely automated and the output consists of millions to billions of short sequences (reads). The following dry bench workflow consists in intensive computational and bioinformatics analyses that use a variety of algorithms that, for instance, (i) map and align the short reads to a linear reference bacterial genome and/or (ii) perform de novo assembly. The EURLs WG on NGS approached the analytic wet bench process and the bioinformatics analyses (''dry bench'') as two discrete processes requiring separate considerations for standards. The EURLs WG have shared a survey to their NRLs network to ask them for different parameters used in the wet and dry lab part of WGS in their laboratories. These parameters are used in this guidance to present the different steps of WGS.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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