MiSTIC, an integrated platform for the analysis of heterogeneity in large tumour transcriptome datasets.
Nucleic Acids Res
; 45(13): e122, 2017 Jul 27.
Article
en En
| MEDLINE
| ID: mdl-28472340
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.
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Biomarcadores de Tumor
/
Perfilación de la Expresión Génica
/
Bases de Datos Genéticas
/
Transcriptoma
Tipo de estudio:
Prognostic_studies
Límite:
Female
/
Humans
Idioma:
En
Revista:
Nucleic Acids Res
Año:
2017
Tipo del documento:
Article
País de afiliación:
Canadá