RESEARCH >> Large Datasets
Massive datasets are generated very quickly in genomics. The computing power required to analyse these whole-genome datasets continuously increases. The reason for the increase in computing capacity is two-fold. Firstly the volume of DNA data in the form of dense marker maps, means an increasing volume of data to be analysed. Secondly, more complex statistical analyses are performed on these large datasets.
The large datasets research programme:
- Identifies strengths and weaknesses of existing statistical methods for analyses of large datasets.
- Develops new methods for analysis of large genome datasets and tools that can be used in sector-specific research.
- Testing these tools using relevant New Zealand datasets from the agriculture, horticulture and forestry sectors and publish results.
- Deliver tools to the New Zealand gene mapping community and scientific community
The main outcome will be development of new methods and delivery of tools for analysing large genome datasets, specifically for economically important species. An additional outcome is to contribute substantially to the international scientific literature. This will build New Zealand’s reputation and competitiveness in biologically-based sectors.
High performance computing and data storage needs will be met through the grid computing network- BeSTGRID (Broadband enabled Science and Technology GRID) and the University of Canterbury supercomputing infrastructure.
KEY PERSONNEL
Statisticians
Rod Ball, Scion, Lead Statistician (Bayesian Statistician)
Ken Dodds, AgResearch, Lead Statistician
Benoit Auvray, AgResearch, Statistician
Mik Black, University of Otago, Lead Statistician and Bioinformaticist
Geneticists
Tony Merriman, University of Otago, Lead Geneticist, and Project Governance Group member and Project Leader
David Chagne, Plant and Food Ltd. Geneticist
John McCallum, Plant and Food Ltd. Geneticist
Paul Fisher, AgResearch. Geneticist
