Fig. 6
From: ModularBoost: an efficient network inference algorithm based on module decomposition
An overview of the ICA-FDR decomposition method. FastICA splits the expression X into a mixing matrix A and a source matrix S. Contained in the rows of S, the components reflect hidden biological processes influencing gene expression. The level of genetic influence on components are reflected by the heat color map, from dark (minimum) to red (maximum). FDR estimation determines which genes are assigned to each module