The Human Toxome Collaboratorium: a shared environment for multi-omic computational collaboration within a consortium

Frontiers in Pharmacology

Dipanwita eRoy Choudhury¹  Rick A Fasani¹  Carolina B Livi¹  Michael eRosenberg¹  Mounir eBouhifd²  Andre eKleensang²  Melvin E Anderson³  Patrick D McMullen³  Salil N Pendse³  Thomas eHartung⁴ 

[1] Agilent Technologies;Bloomberg School of Public Health, Johns Hopkins University;The Hamner Institutes for Health Sciences;University of Konstanz;

关键词: big data;    computational toxicology;    Systems toxicology;    Cloud computing;    virtualization;    virtual machines;   

DOI  :  10.3389/fphar.2015.00322

来源: DOAJ

【 摘 要 】

The Human Toxome Project is part of a long-term vision to modernize toxicity testing for the 21st century. In the initial phase of the project, a consortium of six academic, commercial, and government organizations has partnered to map pathways of toxicity, using endocrine disruption as a model hazard. Experimental data is generated at multiple sites, and analyzed using a range of computational tools. While effectively gathering, managing, and analyzing the data for high-content experiments is a challenge in its own right, doing so for a growing number of -omics technologies, with larger data sets, across multiple institutions complicates the process. Interestingly, one of the most difficult, ongoing challenges has been the computational collaboration between the geographically separate institutions. Existing solutions cannot handle the growing heterogeneous data, provide a computational environment for consistent analysis, accommodate different workflows, and adapt to the constantly evolving methods and goals of a research project. To meet the needs of the project, we have created and managed The Human Toxome Collaboratorium, a shared computational environment hosted on third-party cloud services. The Collaboratorium provides a familiar virtual desktop, with a mix of commercial, open-source, and custom-built applications. It shares some of the challenges of traditional information technology, but with unique and unexpected constraints that emerge from the cloud. Here we describe the problems we faced, the current architecture of the solution, an example of its use, the major lessons we learned, and the future potential of the concept. In particular, the Collaboratorium represents a novel distribution method that could increase the reproducibility and reusability of results from similar large, multi-omic studies.

【 授权许可】

Unknown