PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

GridR: An R-based tool for scientific data analysis in grid environments
Dennis Wegener, Thierry Sengstag, Stelios Sfakianakis, Stefan Rüping and Anthony Assi
Future Generation Computer Systems: The International Journal of Grid Computing: Theory, Methods and Applications Volume 25, Number 4, pp. 481-488, 2009.

Abstract

In this paper, we describe an analysis tool based on the statistical environment R, GridR, which allows using the collection of methodologies available as R packages in a grid environment. It provides the user with transparent and seamless access to large-scale distributed computational services and data repositories within the secure and reliable framework of a grid system. The aim of GridR, which was initiated in the context of the EU project Advancing Clinico-Genomics Trials on Cancer (ACGT), is to provide a powerful framework for the analysis of clinico-genomic trials involving large amount of data (e.g. microarray-based clinical trials). As a proof of the concept, an example of microarray-based analysis taken from the literature was reproduced using GridR.

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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
ID Code:6144
Deposited By:Stefan Rueping
Deposited On:08 March 2010