Abstract 1634: A comprehensive guide for managing large-scale collaborative genomics research projects

Abstract

Abstract Globally applicable best practices guidelines for managing large-scale collaborative genomics projects have been established using lessons learned from the successes and challenges of The Cancer Genome Atlas (TCGA). As the cost of genomic sequencing is decreasing, more and more researchers are leveraging genomic data to inform the biology of disease. The amount of genomic data generated is growing exponentially, and protocols need to be established for the long-term storage, dissemination, and regulation of these data for research. The authors aim to create a comprehensive guide to managing research projects involving genomic data, as learned through the evolution of the TCGA program over the last decade. This project was primarily carried out in the US, but the impact and lessons learned can be applied to an international audience. The guide will serve to: • Establish a framework for managing large-scale genomic research projects involving multiple collaborators •Describe lessons learned through TCGA to prepare for potential roadblocks •Evaluate policy considerations that are needed to avoid pitfalls •Recommend strategies to make project management more efficient • Educate readers on practical considerations and stakeholder applications regarding each step of the project The guide will cover operational procedures, policy considerations, and lessons learned through TCGA on topics such as: •Sample acquisition •Data generation • Data storage and dissemination •Data analysis efforts •Quality control, auditing and reporting •Formation of analysis working groups for consortium publications Analysis of TCGA's programmatic and policy decisions since 2006 provides insight into successful practices. Collaborative spirit, vital to its success, was maintained through incentivizing participation in analysis working groups, publishing with a single network author, and allowing participants to gain early access to project data. TCGA was managed centrally by NIH offices, which streamlined project management activities overall. Sample and clinical data quality was maintained by evaluation of tissue provider practices through a review board, use of a central repository for sample receipt and distribution, and the use of multi-stage payment plan per sample enrolled. Streamlined data analysis, storage, and dissemination occurred through a tightly controlled data coordination center, which among other activities, provided to the public precise datasets used for each analysis publication. Analysis of large-scale genomic information is a complex undertaking with many pitfalls. Best practices guidelines based upon experience in genomics, industrial psychology, data management, and project management will provide a foundation for successful implementation of these projects. Note: This abstract was not presented at the meeting. Citation Format: Margi Sheth, Jiashan Zhang, Jean C. Zenklusen. A comprehensive guide for managing large-scale collaborative genomics research projects. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1634. doi:10.1158/1538-7445.AM2015-1634