The Dynamic Regulatory Events Miner (DREM) software was developed to integrate static protein-DNA interaction data with time series gene expression data for reconstructing dynamic regulatory networks. With additional types of high-throughput time series data now available (miRNA expression, proteomics, epigenomics and single cell RNA-Seq), integrating all available time series and static datasets in a unified model was our new challenge. Enter interactive DREM---iDREM.
iDREM supports all data types mentioned above and, importantly, allows users to interactively visualize a gene, TF, path or model-centric view of each of these data types, their interactions and their impact on the resulting model (shown below). This manual provides information about development and use of the tool. To try the tool with your own data of interest, download the tool from https://github.com/phoenixding/idrem and follow instructions in the manual.
UPDATE: Please see the new publication about the tool:
"We developed a detailed comprehensive and interactive model that provides information about the major expression trajectories, the regulators of specific key events, and the impact of epigenetic changes. Intersecting the model with single cell RNAseq (scRNA-Seq) data led to the identification of active pathways in multiple or individual cell types. We then constructed a similar model for human lung development by profiling time series human omics datasets. Several key pathways and regulators are shared between the reconstructed models. We experimentally validated the activity of a number of predicted regulators leading to new insights about the regulation of innate immunity during lung development."