The application of whole-genome sequence (WGS) technology in regulatory food microbiology provides an unprecedented opportunity to produce highly informative laboratory analyses supporting risk assessment and risk management actions. The quality of WGS datasets will have a significant impact on downstream bioinformatics processes, with one critical element being the possible presence of adventitious DNA sequences due to contamination during sample handling and sequencing operations. This dataset is part of a project aimed to address the need to assure WGS data quality by accounting for contamination events through determination of the impacts of sequencing data contamination events on downstream analyses, such as typing and marker discovery. The goal is to contribute to the development and implementation of harmonized quality protocols for the application of WGS technologies in the international regulatory food microbiology community.
This record consists of three in silico datasets that will be used for proficiency tests. They are organized into mock Illumina MiSeq sequencing runs. The runs consist of the same 24 Escherichia coli samples. FASTQ files for these samples were created by simulating reads from MinION/PacBIO + Illumina MiSeq hybrid-assembly polished genomes or closed reference genomes downloaded from NCBI. Reads were simulated with ART. One run was created using the empirical Illumina MiSeq profile, while the other runs were simulated using custom read profiles generated from over-clustered runs. The reference strains represent a diverse cross-section of serotypes, shiga toxin subtype, antimicrobial resistance (AMR) profiles, plasmid profiles.
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