Abstract
Abstract With the advent of cancer genome analysis, there is an enormous need for an integrative computational approach to understand the functional impact of the genomic aberrations that drive and characterize cancers. This requires mechanisms to aggregate and visualize both public and investigator-generated data on cancer genomes, transcriptomes, epigenomes and more. Extending the UCSC Cancer Genomics Browser, we are developing the UCSC Xena platform to achieve this. UCSC's Xena is a data server-based platform that stores functional genomics data and serves them in response to data requests in real-time and with minimal informatics overhead. Examples of these data requests include data visualization, integration and further downstream analysis. Xena can easily be installed on a laptop, or on servers behind a firewall. The UCSC Xena server provides access to TCGA open access data, with 526 datasets from 31 different TCGA cancer types. Types of hosted datasets include copy number, somatic mutation, DNA methylation, gene and exon expression, protein expression, PARADIGM pathway inference, and phenotype data. Our automated pipeline updates TCGA data periodically, ensuring we are visualizing the most recent data available. Additionally, our pipeline ingests TCGA phenotype data and attempts to assign more readable feature names and values. We further derive overall and recurrence free survival from TCGA phenotype data, allowing users to perform survival analysis. We are extending the UCSC Cancer Genomics Browser to access and visualize data hosted across multiple Xena servers while maintaining data privacy. This functionality allows viewing and interpretation of one's own data (e.g. stored on a private Xena) in the context of a large collection of cancer genomics datasets (e.g. TCGA data stored at UCSC). The outcome is a platform for researchers to store and analyze their datasets in an interoperable manner. We are integrating Xena with other tools such as MuPIT (enables visualization of somatic mutations on three-dimensional protein structures), and with Galaxy to allow integration with other bioinformatics tools such as Trinity (via Galaxy, RNA-seq data analysis to identify coding and non-coding transcripts, score them for aberrations, and quantify their expression). Integrating these tools provides researchers with a workflow with strong analysis and visualization capabilities, and brings sophisticated computational analyses within the reach of non-computational scientists. Citation Format: Jingchun Zhu, Brian Craft, Mary Goldman, Melissa Cline, Mark Diekhans, David Haussler. Using the UCSC Xena Platform to integrate, visualize, and analyze your own data in the context of large external genomic datasets. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B1-07.
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