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    MiSTIC, an integrated platform for the analysis of heterogeneity in large tumour transcriptome datasets

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    Author
    Lemieux, S; Sargeant, T; Laperriere, D; Ismail, H; Boucher, G; Rozendaal, M; Lavallee, V-P; Ashton-Beaucage, D; Wilhelm, B; Hebert, J; ...
    Date
    2017-07-27
    Source Title
    Nucleic Acids Research
    Publisher
    OXFORD UNIV PRESS
    University of Melbourne Author/s
    Hilton, Douglas; SARGEANT, TOBIAS
    Affiliation
    Medical Biology (W.E.H.I.)
    Metadata
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    Document Type
    Journal Article
    Citations
    Lemieux, S., Sargeant, T., Laperriere, D., Ismail, H., Boucher, G., Rozendaal, M., Lavallee, V. -P., Ashton-Beaucage, D., Wilhelm, B., Hebert, J., Hilton, D. J., Mader, S. & Sauvageau, G. (2017). MiSTIC, an integrated platform for the analysis of heterogeneity in large tumour transcriptome datasets. NUCLEIC ACIDS RESEARCH, 45 (13), https://doi.org/10.1093/nar/gkx338.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/256600
    DOI
    10.1093/nar/gkx338
    Abstract
    Genome-wide transcriptome profiling has enabled non-supervised classification of tumours, revealing different sub-groups characterized by specific gene expression features. However, the biological significance of these subtypes remains for the most part unclear. We describe herein an interactive platform, Minimum Spanning Trees Inferred Clustering (MiSTIC), that integrates the direct visualization and comparison of the gene correlation structure between datasets, the analysis of the molecular causes underlying co-variations in gene expression in cancer samples, and the clinical annotation of tumour sets defined by the combined expression of selected biomarkers. We have used MiSTIC to highlight the roles of specific transcription factors in breast cancer subtype specification, to compare the aspects of tumour heterogeneity targeted by different prognostic signatures, and to highlight biomarker interactions in AML. A version of MiSTIC preloaded with datasets described herein can be accessed through a public web server (http://mistic.iric.ca); in addition, the MiSTIC software package can be obtained (github.com/iric-soft/MiSTIC) for local use with personalized datasets.

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