MiSTIC, an integrated platform for the analysis of heterogeneity in large tumour transcriptome datasets
Details
Publication Year 2017-05-04,Volume 45,Issue #13,Page e122
Journal Title
Nucleic Acids Research
Publication Type
Journal Article
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.
Publisher
Oxford Academic
Research Division(s)
Molecular Medicine
PubMed ID
28472340
Terms of Use/Rights Notice
Refer to copyright notice on published article.


Creation Date: 2017-05-30 09:30:48
Last Modified: 2017-09-12 09:10:19
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