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© Research
Publication : BMC research notes

EMA – A R package for Easy Microarray data analysis

Scientific Fields
Diseases
Organisms
Applications
Technique

Published in BMC research notes - 03 Nov 2010

Servant N, Gravier E, Gestraud P, Laurent C, Paccard C, Biton A, Brito I, Mandel J, Asselain B, Barillot E, Hupé P

Link to Pubmed [PMID] – 21047405

BMC Res Notes 2010;3:277

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/.

http://www.ncbi.nlm.nih.gov/pubmed/21047405