metaMA: Wrapper function for effect size or p-value combination...

In MAMA: Meta-Analysis of MicroArray

Description

This is a wrapper function for effect size or p-value combination as implemented in metaMA package.

Usage

metaMA(data, varname, moderated = c("limma", "SMVar", "t")[1], BHth = 0.05, which = c("pval", "ES")[1])

Arguments

data	MetaArray object containing gene expression data matrices, clinical data matrices and a vector of data set names. The gene expression data matrices must have equal rownames
varname	Character String - name of one column in clinical data matrices to be used as class labels
moderated	Character - method to calculate the test statistic (or p-value) inside each study, one of: "limma", "SMVar" and "t"
BHth	Numeric - threshold for Benjamini Hochenberg adjusted p-values for selection of significant genes in meta-analysis
which	Character - choose "pval" for combination of p-values, or "ES" for effect sizes

Value

An object of class "metaMA.res". It is a list where:

Study1	Vector of indices of differentially expressed genes in study 1. Similar names are given for the other individual studies.
AllIndStudies	Vector of indices of differentially expressed genes found by at least one of the individual studies.
Meta	Vector of indices of differentially expressed genes in the meta-analysis.
TestStatistic	Vector with test statistics for differential expression in the meta-analysis.

Author(s)

Ivana Ihnatova

References

Marot, G., Foulley, J.-L., Mayer, C.-D., Jaffrezic, F. Moderated effect size and p-value combinations for microarray meta-analyses.

See Also

pvalcombination, EScombination

Examples

data(ColonData)
pv<-metaMA(ColonData, "MSI", moderated = "t")
  

MAMA documentation built on Jan. 15, 2017, 3:05 p.m.