Package: netboost 2.21.5

netboost: Network Analysis Supported by Boosting

Boosting-supported network analysis for high-dimensional omics data, implementing a three-step dimension reduction technique. A filter combined with the topological overlap measure first identifies the essential edges of the feature network, sparse hierarchical clustering then groups the selected features into modules, and each module is finally summarised by its first principal components. Subsequent analyses are carried out on these low-dimensional module signals instead of the original data, which makes the method well suited to epigenetics, metabolomics, transcriptomics, and other omics studies. The method is described in Schlosser et al. (2021) <doi:10.1109/TCBB.2020.2983010>.

Authors:Pascal Schlosser [aut, cre], Jochen Knaus [aut, ctb], Alex Waterhölter [aut, ctb]