oposSOM: R-package for high-dimensional portraying of genome-wide expression landscapes on bioconductor.

Abstract:

MOTIVATION: Comprehensive analysis of genome-wide molecular data challenges bioinformatics methodology in terms of intuitive visualization with single-sample resolution, biomarker selection, functional information mining and highly granular stratification of sample classes. oposSOM combines those functionalities making use of a comprehensive analysis and visualization strategy based on self-organizing maps (SOM) machine learning which we call 'high-dimensional data portraying'. The method was successfully applied in a series of studies using mostly transcriptome data but also data of other OMICs realms. AVAILABILITY AND IMPLEMENTATION: oposSOM is now publicly available as Bioconductor R package. CONTACT: wirth@izbi.uni-leipzig.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PubMed ID: 26063839

Projects: HNPCC-Sys - Genomic and transcriptomic heterogeneity of colorectal tumou...

Publication type: Not specified

Journal: Bioinformatics

Human Diseases: No Human Disease specified

Citation: Bioinformatics. 2015 Oct 1;31(19):3225-7. doi: 10.1093/bioinformatics/btv342. Epub 2015 Jun 10.

Date Published: 1st Oct 2015

Registered Mode: by PubMed ID

Authors: H. Loffler-Wirth, M. Kalcher, H. Binder

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Created: 6th May 2019 at 12:38

Last updated: 7th Dec 2021 at 17:58

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