title: TCGA Expedition: A Data Acquisition and Management System for TCGA Data.
abstract: BACKGROUND
  The Cancer Genome Atlas Project (TCGA) is a National Cancer Institute effort to profile at least 500 cases of 20 different tumor types using genomic platforms and to make these data, both raw and processed, available to all researchers. TCGA data are currently over 1.2 Petabyte in size and include whole genome sequence (WGS), whole exome sequence, methylation, RNA expression, proteomic, and clinical datasets. Publicly accessible TCGA data are released through public portals, but many challenges exist in navigating and using data obtained from these sites. We developed TCGA Expedition to support the research community focused on computational methods for cancer research. Data obtained, versioned, and archived using TCGA Expedition supports command line access at high-performance computing facilities as well as some functionality with third party tools. For a subset of TCGA data collected at University of Pittsburgh, we also re-associate TCGA data with de-identified data from the electronic health records. Here we describe the software as well as the architecture of our repository, methods for loading of TCGA data to multiple platforms, and security and regulatory controls that conform to federal best practices.
  
  
  RESULTS
  TCGA Expedition software consists of a set of scripts written in Bash, Python and Java that download, extract, harmonize, version and store all TCGA data and metadata. The software generates a versioned, participant- and sample-centered, local TCGA data directory with metadata structures that directly reference the local data files as well as the original data files. The software supports flexible searches of the data via a web portal, user-centric data tracking tools, and data provenance tools. Using this software, we created a collaborative repository, the Pittsburgh Genome Resource Repository (PGRR) that enabled investigators at our institution to work with all TCGA data formats, and to interrogate these data with analysis pipelines, and associated tools. WGS data are especially challenging for individual investigators to use, due to issues with downloading, storage, and processing; having locally accessible WGS BAM files has proven invaluable.
  
  
  CONCLUSIONS
  Our open-source, freely available TCGA Expedition software can be used to create a local collaborative infrastructure for acquiring, managing, and analyzing TCGA data and other large public datasets.
authors: Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States of America.|University of Pittsburgh Cancer Institute, Pittsburgh, PA, United States of America.
authors: Uma R
authors: UR
authors: Chandran
authors: Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States of America.
authors: Olga P
authors: OP
authors: Medvedeva
authors: Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States of America.|Department of Human Genetics, University of Pittsburgh School of Public Health, Pittsburgh, PA, United States of America.|Center for Simulation and Modeling, University of Pittsburgh, Pittsburgh, PA, United States of America.|UPMC Corporate Services, Pittsburgh, PA, United States of America.
authors: M Michael
authors: MM
authors: Barmada
authors: Pittsburgh Supercomputing Center, Carnegie Mellon University, Pittsburgh, PA, United States of America.
authors: Philip D
authors: PD
authors: Blood
authors: Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States of America.|University of Pittsburgh Cancer Institute, Pittsburgh, PA, United States of America.
authors: Anish
authors: A
authors: Chakka
authors: Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States of America.|University of Pittsburgh Cancer Institute, Pittsburgh, PA, United States of America.
authors: Soumya
authors: S
authors: Luthra
authors: Center for Simulation and Modeling, University of Pittsburgh, Pittsburgh, PA, United States of America.
authors: Antonio
authors: A
authors: Ferreira
authors: Center for Simulation and Modeling, University of Pittsburgh, Pittsburgh, PA, United States of America.
authors: Kim F
authors: KF
authors: Wong
authors: University of Pittsburgh Cancer Institute, Pittsburgh, PA, United States of America.|Department of Pharmacology and Cell Biology, University of Pittsburgh, Pittsburgh, PA, United States of America.|Magee-Women's Research Institute, Pittsburgh, PA, United States of America.
authors: Adrian V
authors: AV
authors: Lee
authors: Pittsburgh Supercomputing Center, Carnegie Mellon University, Pittsburgh, PA, United States of America.
authors: Zhihui
authors: Z
authors: Zhang
authors: Pittsburgh Supercomputing Center, Carnegie Mellon University, Pittsburgh, PA, United States of America.
authors: Robert
authors: R
authors: Budden
authors: Pittsburgh Supercomputing Center, Carnegie Mellon University, Pittsburgh, PA, United States of America.
authors: J Ray
authors: JR
authors: Scott
authors: UPMC Corporate Services, Pittsburgh, PA, United States of America.
authors: Annerose
authors: A
authors: Berndt
authors: Institute for Precision Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America.
authors: Jeremy M
authors: JM
authors: Berg
authors: Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States of America.|University of Pittsburgh Cancer Institute, Pittsburgh, PA, United States of America.|Institute for Precision Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America.
authors: Rebecca S
authors: RS
authors: Jacobson
mesh_terms: D003628:Database Management Systems; D023281:Genomics; D006801:Humans; D016247:Information Storage and Retrieval; D009369:Neoplasms / Q000235:genetics*; D012984:Software; D014584:User-Computer Interface