Using the Seven Bridges Cancer Genomics Cloud to Access and Analyze Petabytes of Cancer Data. Issue 1 (8th December 2017)

• Record Type: Journal Article
• Authors: Malhotra, Raunaq; Seth, Isheeta; Lehnert, Erik; Zhao, Jing; Kaushik, Gaurav; Williams, Elizabeth H.; Sethi, Anurag; Davis‐Dusenbery, Brandi N.
• Editors: Bateman, Alex; Pearson, William R.; Stein, Lincoln D.; Stormo, Gary D.; Yates, John R.
• Is Part Of: Current protocols in bioinformatics. Volume 60:Issue 1(2017)
• Page Start: 11.16.1
• Page End: 11.16.32
• Publication Date: 2017-12-08
• Subjects: big data -- cancer genomics -- cloud computing -- common workflow language -- reproducible -- scalable; Bioinformatics -- Laboratory manuals; Nucleotide sequence -- Laboratory manuals; Amino acid sequence -- Laboratory manuals; Base Sequence; Amino Acid Sequence; Computational Biology -- methods; Databases, Genetic; Proteins -- analysis; Sequence Analysis -- methods; Sequence Homology; Amino acid sequence; Bioinformatics; Nucleotide sequence; Laboratory Manuals; Laboratory manuals; 570.285
• DOI: 10.1002/cpbi.39
• Languages: English
• ISSNs: 1934-3396

Abstract

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.