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Last updated: May 15, 2018

Gathering the expertise and project management

Genomic research (and clinical practice) requires a multidisciplinary team, including people with expertise in sequencing technologies, data science (bioinformaticians), and clinical genomics (pathologists, clinical geneticists, clinical scientists and genetic counsellors). Coordination across each of the fields can determine the success of a study.

Have you thought about?

  • Can you consult others working in the field or groups with expertise in genomics research to plan and design the study?
  • Can you collaborate with others to increase statistical power and bring the relevant breadth of expertise to your study, identify a reference group or a mechanism to validate your work?
For more information on multidisciplinary teams see - Gathering the expertise for genomic research
Project management and costs

Multidisciplinary studies, such as clinical genomics research, require appropriate oversight and management.  A well-managed project improves the study’s outcomes and can prevent a raft of issues, such as budget blowouts, loss of data, time delays and misconduct [1] [2].

Tools that can be adapted for a research setting include (but are not limited to):

  • Project plan: an overarching agreement detailing the goals, roles, risks, and budget that helps to track progress and identify issues early
  • Project schedule: a chart or representation that is helpful for coordinating complex processes including the tasks to be completed, their status and their interdependencies
  • Stakeholder register: a record of each stakeholder and team member that promotes good communication and partnerships across a complex project

The key cost of project management is the salary of the project manager, or if you chose not to hire one, the time you spend instead. Beyond funding for project management the resource intensive processes in clinical genomics can include:

  • Funding the multidisciplinary team,
  • Enabling patient-participant interaction before, during and after the project, including return of results (if applicable)
  • Curating samples, coordinating their transfer and tracking of the samples and data throughout the study
  • Data capture to the extent and depth required to draw conclusions
  • Making the project ‘genomic data capable’  
  • Data analysis and interpretation

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[1] Johns A L, McKay S H, Humphris J L, Pinese M, Chantrill L A, Mead R S, et al. (2017) Lost in translation: returning germline genetic results in genome-scale cancer research. Genome medicine. 9(1):41. 

[2] Gaff C L, Winship M I, Forrest S P, Hansen D, Clark J M, Waring P, et al. (2017) Preparing for genomic medicine: a real world demonstration of health system change. Genomic Medicine. 2(1):16.