EMA: Easy Microarray data Analysis

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.

Version: 1.4.4
Depends: R (≥ 2.10)
Imports: siggenes, affy, multtest, survival, xtable, gcrma, heatmap.plus, biomaRt, GSA, MASS, FactoMineR, cluster, AnnotationDbi
Suggests: hgu133plus2.db, lumi, vsn, GOstats, GO.db
Published: 2014-03-28
Author: Nicolas Servant, Eleonore Gravier, Pierre Gestraud, Cecile Laurent, Caroline Paccard, Anne Biton, Jonas Mandel, Bernard Asselain, Emmanuel Barillot, Philippe Hupe
Maintainer: Pierre Gestraud <pierre.gestraud at curie.fr>
License: GPL-3
NeedsCompilation: no
Materials: NEWS
CRAN checks: EMA results

Downloads:

Reference manual: EMA.pdf
Package source: EMA_1.4.4.tar.gz
MacOS X binary: EMA_1.4.4.tgz
Windows binary: EMA_1.4.4.zip
Old sources: EMA archive