Getting Started with Analysis
ISB-CGC enables people to analyze cloud-based cancer data. Learn more about the different analytical methods ISB-CGC users can employ.
Google Cloud Project Setup and Data Access
A Google Cloud Project (GCP) is required to make use of all of the data, tools, and Google Cloud functionality.
Obtain a Google identity
Do you or your institution already have a Google identity, such as a Gmail account? If so, you can proceed to the next step.
If not, it only takes a minute to create a Google identity. You can even link a non-Gmail account (eg. scientist@nih.gov) as a Google identity by this method.
Request Google Cloud Credits
Take advantage of a one-time $300 Google Credit.
If you have already used this one-time offer (or there is some other reason you cannot use it), see this information about how to request ISB-CGC Cloud Credits.
Set up a Google Cloud Project
See Google’s documentation about how to create a Google Cloud Project.
Learn about how to add members and roles to a project.
Connect to ISB-CGC’s cancer data tables in Google BigQuery
To obtain access to the ISB-CGC open access project tables in BigQuery, users can link these tables to their GCP project as described here.
Access open-access data
All individual processed data files are accessible through GDC Google Cloud Storage buckets; ISB-CGC provides pointers to these files. Examples of how to find these URLs are in this section, on each Program’s documentation page; these SQL queries can also be incorporated into notebooks or workflows.
Getting Started with Analysis
Now you’re ready to perform analysis. ISB-CGC offers analysis with Google BigQuery and analysis using APIs and VMs.
Interactive web-based Cancer Data Analysis & Exploration
Explore and analyze ISB-CGC cancer data through a suite of graphical user interfaces (GUIs) that allow users to select and filter data from one or more public data sets (such as TCGA, CCLE, and TARGET), combine these with your own uploaded data and analyze using a variety of built-in visualization tools.
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Cancer data analysis using Google BigQuery
Processed data are consolidated by data type (ex. Clinical, DNA Methylation, RNAseq, Somatic Mutation, Protein Expression, etc.) from sources including the Genomics Data Commons (GDC) and Proteomics Data Commons (PDC) and transformed into ISB-CGC Google BigQuery tables. This allows users to quickly analyze information from thousands of patients in curated BigQuery tables using Structured Query Language (SQL). SQL can be used from the Google BigQuery Console but can also be embedded within Python, R and complex workflows, providing users with flexibility. The easy, yet cost effective, “burstability” of BigQuery allows you to, within minutes (as compared to days or weeks on a non-cloud based system), calculate statistical correlations across millions of combinations of data points.
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Cancer data analysis using APIs & Google Cloud Virtual Machines
ISB-CGC enables the use of as many workflow technologies as possible through documentation, support, and necessary infrastructure.
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