Benchmark datasets for SARS-CoV-2 surveillance bioinformatics.

Xiaoli L, Hagey JV, Park DJ, Gulvik CA, Young EL, Alikhan NF, Lawsin A, Hassell N, Knipe K, Oakeson KF, Retchless AC, Shakya M, Lo CC, Chain P, Page AJ, Metcalf BJ, Su M, Rowell J, Vidyaprakash E, Paden CR, Huang AD, Roellig D, Patel K, Winglee K, Weigand MR, Katz L. (2022)

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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of coronavirus disease 2019 (COVID-19), has spread globally and is being surveilled with an international genome sequencing effort. Surveillance consists of sample acquisition, library preparation, and whole genome sequencing. This has necessitated a classification scheme detailing Variants of Concern (VOC) and Variants of Interest (VOI), and the rapid expansion of bioinformatics tools for sequence analysis. These bioinformatic tools are means for major actionable results: maintaining quality assurance and checks, defining population structure, performing genomic epidemiology, and inferring lineage to allow reliable and actionable identification and classification. Additionally, the pandemic has required public health laboratories to reach high throughput proficiency in sequencing library preparation and downstream data analysis rapidly. However, both processes can be limited by a lack of a standardized sequence dataset.

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