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This article is part of the supplement: BioSysBio: Bioinformatics and Systems Biology Conference

Open Access Open Badges Poster presentation

System level visualization of eQTLs and pQTLs

Joanna Jakubowska*, Ela Hunt, Matthew Chalmers, David Leader, Martin McBride and Anna F Dominiczak

Author Affiliations

Department of Computer Science, University of Glasgow, UK

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BMC Bioinformatics 2005, 6(Suppl 3):P15  doi:10.1186/1471-2105-6-S3-P15

The electronic version of this article is the complete one and can be found online at:

Published:21 September 2005


Poster presentation

Effective visualisation of syntenic genome areas and QTLs derived from physiological and expression data is an unresolved issue. We are investigating genomic visualizations including SyntenyVista2 and Der Browser3 in order to establish the best way to integrate and display these data, and support the use of synteny in the identification of genes responsible for cardiovascular phenotypes. We are showing information regarding eQTLs and pQTLs for the rat1 integrated with data from

. Initial data representation uses Der Browser. We are also integrating the addition of further data from the
. In the next step we will serve these data using SyntenyVista and possibly some other package.

Genomics visualization programs such as SyntenyVista,

    Apollo webcite,
    Artemis webcite,
    BugView webcite,
    Der Browser webcite,
    Ensembl webcite,
    ACT webcite, and RatView are possible candidates in this investigation. We are comparing the systems in terms of functionality, ease of use, data coverage, and support for data analysis. Our aim is to characterize the space of possible solutions in order to choose the most effective ones. At the moment the information is more clearly presented in SyntenyVista, but we still do not have all the relevant information that the biologists wish to see, and do not have a solution for database connectivity, although it might be possible to adapt this from Apollo. Current work is addressing these concerns. User tests are now being planned to assess the effectiveness of our methodology.


  1. Hubner N, et al.: Integrated transcriptional profiling and linkage analysis for identification of genes underlying disease.

    Nature Genetics 2005, 37:243-253. PubMed Abstract | Publisher Full Text OpenURL

  2. Hunt E, et al.: The visual language of synteny.

    OMICS 2004, 8(4):289-305. PubMed Abstract | Publisher Full Text OpenURL

  3. Leser U, et al.: IXDB, an X chromosome integrated database.

    NAR 1997, 26(1):108-111. Publisher Full Text OpenURL