Learn R Programming

metaMA (version 3.1.3)

metaMA-package: Meta-analysis for MicroArrays

Description

Combines either p-values or moderated effect sizes from different studies to find differentially expressed genes.

Arguments

Details

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.

References

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.

Examples

Run this code
# NOT RUN {
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")
  }
# }

Run the code above in your browser using DataLab