Your browser doesn't support javascript.
loading
From SARS-CoV-2 to Global Preparedness: A Graphical Interface for Standardised High-Throughput Bioinformatics Analysis in Pandemic Scenarios and Surveillance of Drug Resistance.
Cumlin, Tomas; Karlsson, Ida; Haars, Jonathan; Rosengren, Maria; Lennerstrand, Johan; Pimushyna, Maryna; Feuk, Lars; Ladenvall, Claes; Kaden, Rene.
Afiliação
  • Cumlin T; Department of Medical Sciences, Section for Clinical Microbiology, Uppsala University, Akademiska Sjukhuset Entrance 40, 751 85 Uppsala, Sweden.
  • Karlsson I; Clinical Genomics Uppsala, Science for Life Laboratory, Uppsala University, 751 85 Uppsala, Sweden.
  • Haars J; Department of Medical Sciences, Section for Clinical Microbiology, Uppsala University, Akademiska Sjukhuset Entrance 40, 751 85 Uppsala, Sweden.
  • Rosengren M; Department of Medical Sciences, Section for Clinical Microbiology, Uppsala University, Akademiska Sjukhuset Entrance 40, 751 85 Uppsala, Sweden.
  • Lennerstrand J; Department of Medical Sciences, Section for Clinical Microbiology, Uppsala University, Akademiska Sjukhuset Entrance 40, 751 85 Uppsala, Sweden.
  • Pimushyna M; Department of Medical Sciences, Section for Clinical Microbiology, Uppsala University, Akademiska Sjukhuset Entrance 40, 751 85 Uppsala, Sweden.
  • Feuk L; National Genomics Infrastructure Uppsala, Uppsala University, 751 08 Uppsala, Sweden.
  • Ladenvall C; Department of Immunology, Genetics and Pathology, Uppsala University, 751 08 Uppsala, Sweden.
  • Kaden R; Clinical Genomics Uppsala, Science for Life Laboratory, Uppsala University, 751 85 Uppsala, Sweden.
Int J Mol Sci ; 25(12)2024 Jun 17.
Article em En | MEDLINE | ID: mdl-38928350
ABSTRACT
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.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Filogenia / Software / Biologia Computacional / Pandemias / SARS-CoV-2 / COVID-19 Limite: Humans Idioma: En Revista: Int J Mol Sci Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Suécia

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Filogenia / Software / Biologia Computacional / Pandemias / SARS-CoV-2 / COVID-19 Limite: Humans Idioma: En Revista: Int J Mol Sci Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Suécia