The ISB Cancer Gateway in the Cloud(link is external) (ISB-CGC) offers multiple avenues for accessing and analyzing large-scale cancer datasets, including TCGA, TARGET, CPTAC and important references such as GENCODE and COSMIC. ISB-CGC users can process petabytes of data using complex workflows written in the language of their choice (including but not limited to CWL, WDL, Snakemake, Nextflow, etc). They can develop new analyses using SQL, Python, and R to mine data including gene expression, protein abundance, and somatic mutations in easily accessible and queryable tables. Updated interactive web tools at isb-cgc.org (link is external)allow cohort creation, data discovery, and exploration. In our cloud computing session, we will demonstrate common bioinformatic workflows using both Python and R while integrating various omic data types such as gene mutations, copy number, gene expression, methylation, and proteomics. We will show how this can be interactively and iteratively performed in the cloud using the ISB-CGC platform.  Attendees will receive hands-on training on optimizing analyses using “burstable” cloud tools, which enables the user to rapidly combine and interrogate their cancer datasets with those available at the Cancer Research Data Commons.