GLUE: a flexible software system for virus sequence data

Singer, J. B., Thomson, E. C. , McLauchlan, J. , Hughes, J. and Gifford, R. J. (2018) GLUE: a flexible software system for virus sequence data. BMC Bioinformatics, 19, 532. (doi:10.1186/s12859-018-2459-9) (PMID:30563445) (PMCID:PMC6299651)

Singer, J. B., Thomson, E. C. , McLauchlan, J. , Hughes, J. and Gifford, R. J. (2018) GLUE: a flexible software system for virus sequence data. BMC Bioinformatics, 19, 532. (doi:10.1186/s12859-018-2459-9) (PMID:30563445) (PMCID:PMC6299651)

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Abstract

Background: Virus genome sequences, generated in ever-higher volumes, can provide new scientific insights and inform our responses to epidemics and outbreaks. To facilitate interpretation, such data must be organised and processed within scalable computing resources that encapsulate virology expertise. GLUE (Genes Linked by Underlying Evolution) is a data-centric bioinformatics environment for building such resources. The GLUE core data schema organises sequence data along evolutionary lines, capturing not only nucleotide data but associated items such as alignments, genotype definitions, genome annotations and motifs. Its flexible design emphasises applicability to different viruses and to diverse needs within research, clinical or public health contexts. Results: HCV-GLUE is a case study GLUE resource for hepatitis C virus (HCV). It includes an interactive public web application providing sequence analysis in the form of a maximum-likelihood-based genotyping method, antiviral resistance detection and graphical sequence visualisation. HCV sequence data from GenBank is categorised and stored in a large-scale sequence alignment which is accessible via web-based queries. Whereas this web resource provides a range of basic functionality, the underlying GLUE project can also be downloaded and extended by bioinformaticians addressing more advanced questions. Conclusion: GLUE can be used to rapidly develop virus sequence data resources with public health, research and clinical applications. This streamlined approach, with its focus on reuse, will help realise the full value of virus sequence data.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Gifford, Dr Robert and Thomson, Dr Emma and Hughes, Dr Joseph and McLauchlan, Professor John and Singer, Dr Joshua
Authors: Singer, J. B., Thomson, E. C., McLauchlan, J., Hughes, J., and Gifford, R. J.
College/School:College of Medical Veterinary and Life Sciences > Institute of Infection Immunity and Inflammation
Journal Name:BMC Bioinformatics
Publisher:BioMed Central
ISSN:1471-2105
ISSN (Online):1471-2105
Copyright Holders:Copyright © 2018 The Authors
First Published:First published in BMC Bioinformatics 19: 532
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
656341Virus-host interactions in hepatitis C virus infectionJohn McLauchlanMedical Research Council (MRC)MC_UU_12014/1MVLS III - CENTRE FOR VIRUS RESEARCH
3007420Accelerating Precision Diagnostics - Bridging the GapAnna DominiczakMedical Research Council (MRC)MC_PC_16045CAMS - Cardiovascular Science
645101T-cell mediated evolution of hepatitis C virus during acute infectionEmma ThomsonWellcome Trust (WELLCOTR)102789/Z/13/ZMVLS III - CENTRE FOR VIRUS RESEARCH