RankProduct: Wrapper function for RankProduct method

In MAMA: Meta-Analysis of MicroArray

Description

This is a wrapper function for perfoming meta-analysis using Rank Product method.

Usage

RankProduct(data, varname, num.perm = 100, logged = TRUE, na.rm = FALSE, gene.names = NULL, plot = FALSE, rand = NULL, cutoff = 0.05)

Arguments

data	MetaArray object
varname	Character String - name of one column in clinical data matrices to be used as class labels, factors are turned into a numeric vector by as.numeric()-1)
num.perm	Number of permutations
logged	Logical - indicating whether data are on log-scale
na.rm	Logical - if FALSE (default), the NA value will not be used in computing rank. If TRUE the missing values will be replaced by the genewise mean of the non-missing values. Gene will all value missing will be assigned "NA"
gene.names	Character vector - gene names to be be attached to the estimated percentage of false prediction (pfp)
plot	Logical - if TRUE a plot of the estimated pfp verse the rank of each gene is drawn
rand	Numeric - a seed for random number generator
cutoff	Numeric - p-value for selection of significant genes

Value

Object of class RankProduct.res containing outputs from functions: RPadvance and topGene. 'Class1' refers to the first level of the used class labels, 'Class2' to the second one.

Author(s)

Ivana Ihnatova

References

Breitling, R., Armengaud, P., Amtmann, A., and Herzyk, P.(2004) Rank Products: A simple, yet powerful, new method to detect differentially regulated genes in replicated microarray experiments, FEBS Letter, 57383-92

Examples

## Not run: 
data(ColonData)
rp<-RankProduct(ColonData, "MSI", num.perm=10)

## End(Not run)

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