Skip to Main content Skip to Navigation
Journal articles

EMA - A R package for Easy Microarray data analysis.

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
Complete list of metadatas

Cited literature [15 references]  Display  Hide  Download
Contributor : Ed. Bmc <>
Submitted on : Monday, April 28, 2014 - 5:11:57 PM
Last modification on : Tuesday, September 22, 2020 - 3:55:41 AM
Long-term archiving on: : Monday, July 28, 2014 - 12:11:45 PM



Nicolas Servant, Eleonore Gravier, Pierre Gestraud, Cecile Laurent, Caroline Paccard, et al.. EMA - A R package for Easy Microarray data analysis.. BMC Research Notes, BioMed Central, 2010, 3 (1), pp.277. ⟨10.1186/1756-0500-3-277⟩. ⟨inserm-00984710⟩



Record views


Files downloads