NCI Office of Data Sharing (ODS) Data Jamboree (Abstract Submissions): Submission #12

Abstract Summary To recognize clinically important intrinsic cancer subtypes, it is important to combine multi-omics datasets to find multi-omics clusters, and the interrelationships between biomolecules and their functions. Here, we will use unsupervised clustering using information from at least two data types to search for subgroups of interests. Next, we will use our Multi-omics Pathways Workflow, an automated Multi-omics Workflow on the Cancer Genomics Cloud to search for activated molecular pathways for each subgroup. The omics data could include copy number alterations, transcriptomics data, proteomics and phospho-proteomics data.The distinct pathways for subgroups found by unsupervised clustering will be displayed graphically (e.g., in heatmaps) to facilitate interpretation with clinical data.