Getting Started with Analysis

ISB-CGC enables researchers to analyze cloud-based cancer data through a collection of powerful web-based tools and Google Cloud technologies. Learn more about the different analytical methods ISB-CGC users employ on their research projects.

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.

Cohort Builder/Data Explorer Create and explore cohorts of interest	ISB-CGC Cohort Builder/Data Explorer Documentation ISB-CGC Cohort Builder/Data Explorer
Interactive Pathology and Radiology Image Viewers View images from cancer patients using integrated image viewers	ISB-CGC Image Viewers Documentation
Integrative Genomics Viewer (IGV) Explore and visualize genomic data	ISB-CGC Integrative Genomics Viewer (IGV) Documentation
Cancer Data File Browser Browse and identify files associated with cohorts of interest	ISB-CGC Cancer Data File Browser Documentation ISB-CGC Cancer Data File Browser
Mitelman Database for Chromosome Aberrations and Gene Fusions in Cancer Explore relationships between chromosomal changes and cancer	ISB-CGC Mitelman Database Documentation ISB-CGC Mitelman Database
The TP53 Database Explore TP53 variant data that have been reported in the published literature or are available in other public databases.	ISB-CGC The TP53 Database Documentation ISB-CGC The TP53 Database

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.

BigQuery Table Search User Interface Learn more about ISB-CGC hosted BigQuery tables	ISB-CGC BigQuery Table Search Documentation ISB-CGC BigQuery Table Search
Google BigQuery Console Use SQL to analyze and query ISB-CGC cancer data stored in Google’s cloud-based data warehouse	ISB-CGC BigQuery Documentation Google BigQuery Documentation Google Cloud BigQuery Console
Notebooks Seamlessly integrate ISB-CGC tables with R and Python to conduct robust analyses	ISB-CGC Notebook Documentation ISB-CGC Statistical Notebook Documentation

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.

ISB-CGC APIs Programmatically access data and user-generated cancer patient cohort information	ISB-CGC API Documentation ISB-CGC API
Connecting to GA4GH and Cloud Life Sciences APIs: Easily connect to APIs from ISB-CGC	How to find a tool using GA4GH TRS Notebook How to use a GA4GH tool using WES Notebook Google API Documentation
Running workflows on ISB-CGC Execute open-source and custom pipelines/algorithms on scalable virtual machines	ISB-CGC Workflow Documentation We recommend tools such as the Google Cloud SDK, Google Compute Engine, Virtual Machines and Docker to assist your analyses.

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