EMA - A R package for Easy Microarray data analysis

Abstract

Abstract Background The increasing number of methodologies and tools currently available to analyse gene expression microarray data can be confusing for non specialist users. Findings Based on the experience of biostatisticians of Institut Curie, we propose both a clear analysis strategy and a selection of tools to investigate microarray gene expression data. The most usual and relevant existing R functions were discussed, validated and gathered in an easy-to-use R package (EMA) devoted to gene expression microarray analysis. These functions were improved for ease of use, enhanced visualisation and better interpretation of results. Conclusions Strategy and tools proposed in the EMA R package could provide a useful starting point for many microarrays users. EMA is part of Comprehensive R Archive Network and is freely available at http://bioinfo.curie.fr/projects/ema/.