Using the Seven Bridges Cancer Genomics Cloud to Access and Analyze Petabytes of Cancer Data
Raunaq Malhotra, Isheeta Seth, Erik Lehnert, Jing Zhao, Gaurav Kaushik, Elizabeth H. Williams, Anurag Sethi, Brandi N. Davis-Dusenbery
下载PDF
{"title":"Using the Seven Bridges Cancer Genomics Cloud to Access and Analyze Petabytes of Cancer Data","authors":"Raunaq Malhotra, Isheeta Seth, Erik Lehnert, Jing Zhao, Gaurav Kaushik, Elizabeth H. Williams, Anurag Sethi, Brandi N. Davis-Dusenbery","doi":"10.1002/cpbi.39","DOIUrl":null,"url":null,"abstract":"<p>Next-generation sequencing has produced petabytes of data, but accessing and analyzing these data remain challenging. Traditionally, researchers investigating public datasets like The Cancer Genome Atlas (TCGA) would download the data to a high-performance cluster, which could take several weeks even with a highly optimized network connection. The National Cancer Institute (NCI) initiated the Cancer Genomics Cloud Pilots program to provide researchers with the resources to process data with cloud computational resources. We present protocols using one of these Cloud Pilots, the Seven Bridges Cancer Genomics Cloud (CGC), to find and query public datasets, bring your own data to the CGC, analyze data using standard or custom workflows, and benchmark tools for accuracy with interactive analysis features. These protocols demonstrate that the CGC is a data-analysis ecosystem that fully empowers researchers with a variety of areas of expertise and interests to collaborate in the analysis of petabytes of data. © 2017 by John Wiley & Sons, Inc.</p>","PeriodicalId":10958,"journal":{"name":"Current protocols in bioinformatics","volume":"60 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2017-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/cpbi.39","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current protocols in bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cpbi.39","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Biochemistry, Genetics and Molecular Biology","Score":null,"Total":0}
引用次数: 4
引用
批量引用
Abstract
Next-generation sequencing has produced petabytes of data, but accessing and analyzing these data remain challenging. Traditionally, researchers investigating public datasets like The Cancer Genome Atlas (TCGA) would download the data to a high-performance cluster, which could take several weeks even with a highly optimized network connection. The National Cancer Institute (NCI) initiated the Cancer Genomics Cloud Pilots program to provide researchers with the resources to process data with cloud computational resources. We present protocols using one of these Cloud Pilots, the Seven Bridges Cancer Genomics Cloud (CGC), to find and query public datasets, bring your own data to the CGC, analyze data using standard or custom workflows, and benchmark tools for accuracy with interactive analysis features. These protocols demonstrate that the CGC is a data-analysis ecosystem that fully empowers researchers with a variety of areas of expertise and interests to collaborate in the analysis of petabytes of data. © 2017 by John Wiley & Sons, Inc.
使用七桥癌症基因组云访问和分析数pb的癌症数据
下一代测序已经产生了数拍字节的数据,但访问和分析这些数据仍然具有挑战性。传统上,研究人员调查像癌症基因组图谱(TCGA)这样的公共数据集,需要将数据下载到高性能集群,即使在高度优化的网络连接下,这也需要几周的时间。美国国家癌症研究所(NCI)启动了癌症基因组学云试点项目,为研究人员提供使用云计算资源处理数据的资源。我们提出了使用这些云试点之一的协议,七桥癌症基因组云(CGC),查找和查询公共数据集,将您自己的数据带到CGC,使用标准或自定义工作流程分析数据,以及具有交互式分析功能的准确性基准工具。这些协议表明,CGC是一个数据分析生态系统,充分授权具有各种专业知识和兴趣领域的研究人员在pb级数据分析中进行合作。©2017 by John Wiley &儿子,Inc。
本文章由计算机程序翻译,如有差异,请以英文原文为准。