Cancer has many different molecular mechanisms to disrupt cellular pathways, which result in uncontrolled cell proliferation (1–3
). Fortunately, development of high-throughput genomic technologies in recent years has greatly increased the amount of data available to researchers to investigate these mechanisms. Not only have the number of patients which have genomic data increased, but also the amount and type of data available per patient has grown. In addition, valuable clinical information from patients and their tumors are often available to researchers alongside of these genomic information.
Despite this wealth of data, analysis of the cancer genome can be challenging due to the limitations in current technologies to visualise, integrate, compare and analyse cancer genomics data. These data, and the conclusions they support, must be presented in a coherent system for display and analysis as well as be accessible to the scientific and medical communities. The UCSC Cancer Genomics Browser (https://genome-cancer.ucsc.edu
) was developed to display these expanding data sources in an integrative, interactive and versatile way as well as help facilitate comprehensive analysis of cancer genomics and its associated clinical data (4
The browser is a web-based tool to integrate, visualise and analyse genomic and clinical information. Experimental measurements for multiple samples are displayed alongside their associated clinical information. Multiple datasets can be viewed simultaneously allowing comparison across studies and between different data types, such as gene expression and copy number variation. The browser provides interactive and dynamic views of the data from whole-genome to base-pair scale resolution, as well as zooming to a subset of samples. Users can interactively group samples by common clinical features such as response to chemotherapy, or by genomic signatures that predict response to a drug. Viewing genomic data by genes allows users to easily see functional changes to the genome as well as examine trends across pathways of genes. Several statistical tools are available making it possible to obtain quantitative results dynamically. Additionally, the Tumor Image Viewer, based on Google Maps, allows users to interactively view slides of tumor tissue samples.
The browser currently contains 355 datasets corresponding to genome-wide experiments on 71 870 samples, most of which are from The Cancer Genome Atlas project (TCGA, https://tcga-data.nci.nih.gov/tcga/
). Data on the website are updated periodically to include the latest releases from TCGA and other projects. Currently, the browser holds 201 TCGA public-tier datasets from 22 TCGA cancer projects, data from the Cancer Cell Line Encyclopedia project (CCLE, http://www.broadinstitute.org/ccle/home
), and 43 other published studies. The Google-maps-based microscope slide viewer has 2433 slides from TCGA.
In the past 2 years, we have made significant changes to the browser including improving the user interface, as well as implementing user accounts, an online tutorial and better documentation. The data versioning system we developed this year, allows us to offer users the ability to download datasets. We also released a new Tumor Image Browser, based on Google Maps, that offers intuitive panning and zooming across microscope slide images.