Portraying the Expression Landscapes of B-CellLymphoma-Intuitive Detection of Outlier Samples and of Molecular Subtypes
We present an analytic framework based on Self-Organizing Map (SOM) machine learning to study large scale patient data sets.The chervo jacke herren potency of the approach is demonstrated in a case study using gene expression data of more than 200 mature aggressive B-cell lymphoma patients.The method portrays each sample with individual resolution,