metaMA-package | R Documentation |
Combines either p-values or moderated effect sizes from different studies to find differentially expressed genes.
Package: | metaMA |
Type: | Package |
Version: | 3.1.2 |
Date: | 2015-01-28 |
License: | GPL |
LazyLoad: | yes |
pvalcombination
and EScombination
are the most important functions to combine unpaired data.
pvalcombination
combines p-values from individual studies.
EScombination
combines effect sizes from individual studies.
pvalcombination.paired
and EScombination.paired
are to be used for paired data.
IDDIDR
can help in the interpretation of gain and loss of information due to meta-analysis.
Guillemette Marot <guillemette.marot@inria.fr>
Marot, G., Foulley, J.-L., Mayer, C.-D., Jaffrezic, F. (2009) Moderated effect size and p-value combinations for microarray meta-analyses. Bioinformatics. 25 (20): 2692-2699.
library(metaMA) data(Singhdata) EScombination(esets=Singhdata$esets,classes=Singhdata$classes) pvalcombination(esets=Singhdata$esets,classes=Singhdata$classes) #more details are provided in the vignette; only open it in interactive R sessions if(interactive()){ vignette("metaMA") }
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