PROGRAMS & DATA

multiSOMe

oposSOM

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.

http://master.bioconductor.org/packages/devel/bioc/html/oposSOM.html

https://github.com/hloefflerwirth/oposSOM