Abstract
Abstract UCSC Xena (http://xena.ucsc.edu/) is a web-based visual integration and exploration tool for multi-omic data and associated clinical and phenotypic annotations. Our unique Visual Spreadsheet shows multiple data types side-by-side enabling discovery of correlations across and within genes and genomic regions. We offer dynamic Kaplan-Meier survival analysis, powerful filtering and subgrouping, charts, statistical analyses, genomic signatures, comparative transcript views, and bookmarks. We link out to the UCSC Genome Browser, giving users additional genomic context for any gene or coordinate, as well as MuPIT/CRAVAT and TumorMap, to give users complementary views of the same data. Xena showcases seminal cancer genomics datasets from TCGA, the Pan-Cancer Atlas, PCAWG, GDC, GTEx, ICGC, and more; a total of more than 1500 datasets across 50 cancer types. We support virtually any type of functional genomics data. In addition to the commonly available SNPs, INDELs, copy number variation, and gene expression datasets, we support DNA methylation, exon-, transcript-, miRNA-, lncRNA-expression and structural variants. We also support clinical data such as phenotypes, subtype classifications and biomarkers. A recompute of TCGA, TARGET and GTEx datasets through the same bioinformatics pipeline allows users to compare expression between tumor and normal tissues. All of our data is available for download via our python API or through AWS S3 buckets. A researcher can host their own data securely via private hubs running on a laptop or behind a firewall, with visual and analytical integration occurring only within the Xena Browser. The lightweight Xena Data Hubs are straightforward to install on Windows, Mac and Linux. Loading data is easy using either our application or command line interface. Our newest features include: * a new, more intuitive wizard to load your data into a local Hub * URL bookmarks to save interactive views for yourself or to share with collaborators * genomic signatures: dynamically build as a weighted sum over a set of genes * hierarchically cluster a list of genes, regulons or probes * upper vs lower quartile in a KM plot Citation Format: Mary Goldman, Brian Craft, Jingchun Zhu, David Haussler. UCSC Xena for cancer genomics visualization and interpretation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 911.
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