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: |
1.4.0 |
| Depends: |
R (≥ 2.10), cluster, heatmap.plus, FactoMineR, GOstats, survival, multtest, gcrma, GSA, siggenes, MASS, biomaRt, xtable, AnnotationDbi |
| Suggests: |
hgu133plus2.db, lumi, vsn |
| Published: |
2013-04-29 |
| 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 |
| CRAN checks: |
EMA results |