Multi-Omics and NETwork Analysis Summer Workshop (MONET) - For more than a decade genome-wide association studies (GWAS) have provided insight into the genetic basis of a variety of complex diseases, physiological traits, and molecular phenotypes. Biomedical researchers are increasingly linking genome wide data (e.g., DNA variants, DNA methylation, chromatin accessibility) with other high-throughput molecular data (e.g., transcripts, proteins, metabolites). These additional omics technologies have been useful for extending the biological relevance of GWAS findings by providing functional interpretation of GWAS signals, biomarker identification, disease subtyping, and understanding of molecular processes that underlie disease etiology in relevant tissues. Despite the promise offered by multi-omics data, analysis is often challenging due to multiple large and high-dimensional data sets; heterogeneity across technologies, coverage, range, and signal quality; decisions about how and when to integrate data; and the lack of data from diverse subjects. The multi-omics field is quickly evolving, and we and others have developed methodology regarding multi-omics analyses. In particular, network science and graph analytics has been an intuitive framework for identifying interactions across omics modalities. In response to PAR-22-095 (“National Human Genome Research Institute (NHGRI) Short Courses for Genomics-Related Research Education”), we have developed the Multi-Omics and NETwork analysis workshop (MONET) to provide an interactive experience to learn about multi-omics analysis and the application of network methods. The MONET training would complement the mission of NHGRI as genetic analyses are frequently being integrated with other omics profiles and it is increasingly important to have a trained workforce that has familiarity with multi-omics tools. For MONET, we propose a 7-day immersive experience for ~25 researchers each summer 2024-2028. MONET will consist of ~50 hours of lectures, discussion sessions, computational labs, and tours. Each day will include didactic portions providing overviews of the technologies and methods. The rest of the time will primarily be devoted to hands-on sessions where participants will implement methods using provided sample code and data sets. So that participants also understand how data are generated, we will organize tours of our technology cores, in addition to an outing to an industry partner. We will also include discussion sessions on cross-cutting topics for multi-omics research including omics data preparation, harmonization, and computing, in addition to omics data sharing, privacy and policy issues. Finally, multi-omics research requires a team science approach which will be developed through group exercises. Participants will be post-baccalaureate researchers (e.g., MS/PhD students, research staff, post-doctoral fellows, clinical fellows, junior and senior research investigators) who have interest in analyzing multi-omics data and sufficient programming knowledge to follow data analysis procedures. Instructors will be drawn from experts with experience in genetics, bioinformatics and data science at the University of Colorado Anschutz Medical Campus, affiliated institutions, and external guest lecturers.
