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Genome Detective: an automated system for virus identification from high-throughput sequencing data

Title: Genome Detective: an automated system for virus identification from high-throughput sequencing data
Authors: Vilsker, Michael; Moosa, Yumna; Nooij, Sam; Fonseca, Vagner; Ghysens, Yoika; Dumon, Korneel; Pauwels, Raf; Alcantara, Luiz Carlos; Eynden, Ewout Vanden; Vandamme, Anne-Mieke; Deforche, Koen; de Oliveira, Tulio
Source: ISSN:1367-4803 ; ISSN:1367-4811 ; Bioinformatics, vol. 35 (5), Art.No. 5, (871-873.
Publisher Information: Oxford University Press
Publication Year: 2019
Subject Terms: Science & Technology; Life Sciences & Biomedicine; Technology; Physical Sciences; Biochemical Research Methods; Biotechnology & Applied Microbiology; Computer Science; Interdisciplinary Applications; Mathematical & Computational Biology; Statistics & Probability; Biochemistry & Molecular Biology; Mathematics; ALGORITHM; ALIGNMENT; Drug Delivery Systems; Genome; Viral; High-Throughput Nucleotide Sequencing; Sequence Analysis; DNA; Software; Viruses; 01 Mathematical Sciences; 06 Biological Sciences; 08 Information and Computing Sciences; Bioinformatics; 31 Biological sciences; 46 Information and computing sciences; 49 Mathematical sciences
Description: SUMMARY: Genome Detective is an easy to use web-based software application that assembles the genomes of viruses quickly and accurately. The application uses a novel alignment method that constructs genomes by reference-based linking of de novo contigs by combining amino-acids and nucleotide scores. The software was optimized using synthetic datasets to represent the great diversity of virus genomes. The application was then validated with next generation sequencing data of hundreds of viruses. User time is minimal and it is limited to the time required to upload the data. AVAILABILITY AND IMPLEMENTATION: Available online: http://www.genomedetective.com/app/typingtool/virus/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. ; sponsorship: Supported by a research Flagship grant from the South African Medical Research Council (MRC-RFA-UFSP-01-2013/UKZN HIVEPI), a Royal Society Newton Advanced Fellowship (TdO), the VIROGENESIS project receives funding from the European Union's Horizon 2020 Research and Innovation Program (under Grant Agreement no. 634650) and the National Institutes of Health Common Fund, grant number U24HG006941. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. We would like to acknowledge the contribution of Annelies Kroneman, Harry Vennema, Roel Standaert, Pieter Libin and Kristof Theys. (South African Medical Research Council|MRC-RFA-UFSP-01-2013/UKZN HIVEPI, Royal Society Newton Advanced Fellowship, European Union's Horizon 2020 Research and Innovation Program|634650, National Institutes of Health Common Fund|U24HG006941, National Human Genome Research Institute; NIH Office of the Director|U24HG006941) ; status: Published
Document Type: article in journal/newspaper
File Description: application/pdf
Language: English
Relation: https://lirias.kuleuven.be/handle/123456789/635380; https://doi.org/10.1093/bioinformatics/bty695; https://pubmed.ncbi.nlm.nih.gov/30124794
DOI: 10.1093/bioinformatics/bty695
Availability: https://lirias.kuleuven.be/handle/123456789/635380; https://lirias.kuleuven.be/retrieve/741a093a-bbb9-460c-8f5d-3119251a1c6e; https://doi.org/10.1093/bioinformatics/bty695; https://pubmed.ncbi.nlm.nih.gov/30124794
Rights: info:eu-repo/semantics/openAccess ; public
Accession Number: edsbas.DF0A1ADF
Database: BASE