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From SARS-CoV-2 to Global Preparedness: A Graphical Interface for Standardised High-Throughput Bioinformatics Analysis in Pandemic Scenarios and Surveillance of Drug Resistance.
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- معلومة اضافية
- المصدر:
Publisher: MDPI Country of Publication: Switzerland NLM ID: 101092791 Publication Model: Electronic Cited Medium: Internet ISSN: 1422-0067 (Electronic) Linking ISSN: 14220067 NLM ISO Abbreviation: Int J Mol Sci Subsets: MEDLINE
- بيانات النشر:
Original Publication: Basel, Switzerland : MDPI, [2000-
- الموضوع:
- نبذة مختصرة :
The COVID-19 pandemic highlighted the need for a rapid, convenient, and scalable diagnostic method for detecting a novel pathogen amidst a global pandemic. While command-line interface tools offer automation for SARS-CoV-2 Oxford Nanopore Technology sequencing data analysis, they are inapplicable to users with limited programming skills. A solution is to establish such automated workflows within a graphical user interface software. We developed two workflows in the software Geneious Prime 2022.1.1, adapted for data obtained from the Midnight and Artic's nCoV-2019 sequencing protocols. Both workflows perform trimming, read mapping, consensus generation, and annotation on SARS-CoV-2 Nanopore sequencing data. Additionally, one workflow includes phylogenetic assignment using the bioinformatic tools pangolin and Nextclade as plugins. The basic workflow was validated in 2020, adhering to the requirements of the European Centre for Disease Prevention and Control for SARS-CoV-2 sequencing and analysis. The enhanced workflow, providing phylogenetic assignment, underwent validation at Uppsala University Hospital by analysing 96 clinical samples. It provided accurate diagnoses matching the original results of the basic workflow while also reducing manual clicks and analysis time. These bioinformatic workflows streamline SARS-CoV-2 Nanopore data analysis in Geneious Prime, saving time and manual work for operators lacking programming knowledge.
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- Grant Information:
KAW 2020.0241 Knut and Alice Wallenberg Foundation; ALF-938076 Gullstrand Foundation
- Contributed Indexing:
Keywords: antimicrobial resistance surveillance; automated bioinformatics; high-throughput sequence data analysis; outbreak surveillance; pandemic preparedness
- الموضوع:
Date Created: 20240627 Date Completed: 20240627 Latest Revision: 20240629
- الموضوع:
20240629
- الرقم المعرف:
PMC11204113
- الرقم المعرف:
10.3390/ijms25126645
- الرقم المعرف:
38928350
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