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ACGT Newsletter

View Summer 2010 Issue

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GridR

Download GridR from CRAN

The aim of GridR is to provide a powerful framework for the analysis of clinico-genomic trials involving large amount of data, e.g. microarray-based clinical trials.

GridR is a gridified version of the R statistical environment [http://www.r-project.org]. R provides a broad range of state-of-the-art statistical, graphical techniques and advanced data mining methods (including comprehensive packages for linear and non-linear modelling, cluster analysis, prediction, hypothesis tests, resampling, survival analysis, time-series analysis), it is easy extensible and turned out as the de facto standard for statistical research and many applied statistics project, especially in the biomedical field. The associated project BioConductor [http://www.bioconductor.org] addresses the needs of the biomedical and biostatisticians community for genomic data-analysis oriented R packages. Numerous methods available as R /BioConductor packages and considered experimental a few years ago have been stabilized and became accepted standard in the analysis of high-throughput genomic data. Integrating R /BioConductor in an open-source clinical data-analysis environment is thus provides an interesting tool for the biomedical community.

In the ACGT analysis environment, R is used as a user interface and as an analysis tool. R as user interface is supposed to serve as programming language interface to the ACGT environment. Used as analysis tool, the goal is to achieve a seamless integration of the functionality of R and the ACGT semantic data services in a grid environment, hiding complexity of the grid environment as the user might not want to or is not capable to deal with. Thus, GridR enables users to run experiments in the grid and profit from the advantages of grid technology, such as scalability, security an reliability.

 

References

  • Wegener, Dennis, and Sengstag, Thierry, and Sfakianakis, Stelios and R?ping, Stefan, and Assi, Anthony. GridR: An R-based grid-enabled tool for data analysis in ACGT clinico-genomic trials. In: Proceedings of the 3rd International Conference on e-Science and Grid Computing (eScience 2007), Bangalore, India. http://www.stefan-rueping.de/publications/wegener-etal-2007-a.pdf
  • Tutorial on Distributed Data Analysis using R at UseR 2008. http://www.statistik.uni-dortmund.de/useR-2008/tutorials/rueping.html
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