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

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.

journal_name

Nucleic Acids Res

journal_title

Nucleic acids research

authors

Lemieux S,Sargeant T,Laperrière D,Ismail H,Boucher G,Rozendaal M,Lavallée VP,Ashton-Beaucage D,Wilhelm B,Hébert J,Hilton DJ,Mader S,Sauvageau G

doi

10.1093/nar/gkx338

subject

Has Abstract

pub_date

2017-07-27 00:00:00

pages

e122

issue

13

eissn

0305-1048

issn

1362-4962

pii

3796331

journal_volume

45

pub_type

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