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GLUE: a flexible software system for virus sequence data.

Joshua B Singer1, Emma C Thomson2, John McLauchlan2

  • 1MRC-University of Glasgow Centre for Virus Research, Glasgow, Scotland, UK. josh.singer@glasgow.ac.uk.

BMC Bioinformatics
|December 20, 2018
PubMed
Summary
This summary is machine-generated.

GLUE is a bioinformatics environment that organizes virus genome sequences for better interpretation and response to outbreaks. This data-centric approach facilitates rapid development of resources for public health, research, and clinical applications.

Keywords:
Sequence databaseVirus evolutionVirus genotypingVirus sequence dataWeb-based bioinformatics

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Area of Science:

  • Bioinformatics
  • Virology
  • Genomics

Background:

  • Increasing volumes of virus genome sequences offer scientific insights and aid epidemic response.
  • Scalable computing resources are essential for organizing and processing vast amounts of sequence data.
  • GLUE (Genes Linked by Underlying Evolution) is a bioinformatics environment designed to manage and interpret virus sequence data.

Purpose of the Study:

  • To present GLUE as a data-centric bioinformatics environment for building virus sequence data resources.
  • To demonstrate the flexibility and applicability of GLUE across different viruses and contexts.
  • To showcase HCV-GLUE as a case study for hepatitis C virus (HCV) sequence analysis.

Main Methods:

  • Development of a data-centric core schema (GLUE) for organizing sequence data along evolutionary lines.
  • Inclusion of nucleotide data, alignments, genotype definitions, genome annotations, and motifs.
  • Creation of HCV-GLUE, a specific resource with a public web application for sequence analysis.

Main Results:

  • HCV-GLUE provides an interactive web application for maximum-likelihood genotyping, antiviral resistance detection, and sequence visualization.
  • HCV sequence data from GenBank is organized into a large-scale alignment accessible via web queries.
  • The GLUE project is downloadable and extensible for bioinformaticians addressing advanced research questions.

Conclusions:

  • GLUE enables the rapid development of virus sequence data resources for public health, research, and clinical applications.
  • The streamlined and reusable approach of GLUE maximizes the value of virus sequence data.
  • GLUE supports diverse needs within research, clinical, and public health settings.