Meet MOPAW—A New Tool for Using Multi-omics Data in NCI’s Cancer Genomics Cloud
Have you been wanting to use multi-omics data to look at different genetic pathways underlying cancer, but you lack the necessary coding experience? A new tool from NCI may be able to help.
NCI researchers have developed a fully automated, multi-omics pathway workflow for exploring specific genes/pathways associated with different types of cancers.
“We saw a need for a uniform framework for processing and analyzing multi-omics data from start to finish,” said Dr. Daoud Meerzaman, who led the NCI team, “so we developed a pipeline called Multi-omics Pathway Workflow, or MOPAW.”
MOPAW offers a simple graphical user interface for conducting multivariate, single sample, gene analysis (MOGSA) on the Cancer Genomics Cloud (CGC).
Using the MOGSA tool, the NCI team identified distinct genetic pathways in a high-risk group of adults with Acute Myeloid Leukemia by integrating data (i.e., transcriptomic and copy number variation) from TCGA. They also identified distinct pathways in subtypes from 87 lung adenocarcinoma cases by integrating transcriptomic, proteomic, and phosphoproteomic data derived from the Applied Proteogenomics OrganizationaL Learning and Outcomes (APOLLO) network.
MOPAW makes it easier to use MOGSA and has several advantages over existing tools. With MOPAW, you can use your own data or key public data sets. The workflow also fosters collaboration. You can invite others to join the project, and you can notify them when it’s time to view the results. Using MOPAW, you also can integrate different data types right from the start.
Dr. Meerzaman noted, “One of the biggest advantages is that you don’t need prior coding or command-line experience to apply this tool. You simply upload and input your data files, choose the desired app settings, and run the tasks with a few mouse-clicks.”