Introduction to multiomics integration using COSMOS
Trainer: Aurelien Dugourd
Overview:
COSMOS (Causal Oriented Search of Multi-Omic Space) is a method that integrates phosphoproteomics, transcriptomics, and metabolomics data sets. COSMOS leverages extensive prior knowledge of signaling pathways, metabolic networks, and gene regulation with computational methods to estimate activities of transcription factors and kinases as well as network-level causal reasoning. This pipeline can provide mechanistic explanations for experimental observations across multiple omic data sets.
Essentially, COSMOS find the most parsimonious subnetwork connecting as many deregulated TFs, kinases/phosphatases and metabolites as possible with directly interpretable mechanistic hypotheses. The subnetwork is extracted from a novel integrated Prior Knowledge Network spanning signaling, transcriptional regulation and metabolism, using prior knowledge extracted from Omnipath, STITCHdb and Recon3. Transcription factors activities are inferred from gene expression with DoRothEA, a meta resource of TF/target links. Kinase activities are inferred from phosphoproteomic with a kinase/substrate network of Omnipath, a meta resource of protein-protein interactions.
Learning outcomes
By the end of this lecture you will be able to:
- Explore using COSMOS for data integration
- Describe how COSMOS works
Materials: