Abstract 2274: Cancer genomics visualization and interpretation using UCSC Xena
暂无分享,去创建一个
The UCSC Xena platform (http://xena.ucsc.edu/) allows biologists and bioinformaticians to securely analyze and visualize functional genomics data. Our unique Visual Spreadsheet shows multiple data types side by side enabling discovery of correlations across and within genes and genomic regions. Dynamic Kaplan-Meier survival analysis assesses survival stratification in addition to scatter plots, bar graphs, and boxplots all shown with statistical tests. In addition to the commonly available SNPs, INDELs, CNV, 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. Our new whole genome views allow users to easily visualize non-coding regions for both copy number variation and somatic mutations. All of our data is available for download via our python API or through AWS S3 buckets. Our expanding public Xena Data Hubs currently host 1500+ datasets from more than 35 cancer types, as well as Pan-Cancer datasets. In addition to serving seminal cancer genomic datasets to the scientific community, including the latest from the GDC, TCGA, TARGET, and ICGC, we also host 9normal tissue9 datasets from GTEx. A recompute of TCGA, TARGET and GTEx datasets through the same bioinformatics pipeline allows users to compare expression between tumor and normal tissues. In addition to exploring these public datasets, the UCSC Xena Browser can easily display an investigator9s genomic and clinical data on their own Xena Hub. By empowering users to install and load data into their own hub, our architecture ensures that the investigator9s data remains private. The lightweight Xena Data Hubs are straightforward to install on Windows, Mac and Linux operating systems and loading data is easy using either our application or command line interface. Citation Format: Mary Goldman, Brian Craft, Jingchun Zhu, David Haussler. Cancer genomics visualization and interpretation using UCSC Xena [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2274.