foldchange: Compute foldchange

In EMA: Easy Microarray Data Analysis

Description

Caculates the foldchange for each genes.

Usage

foldchange(data, labels, unlog = TRUE)

Arguments

data	A matrix or a data frame of expression data. Each row of 'data' must correspond to a gene, and each column to a sample.
labels	A vector of length 'ncol(data)' containing the class labels of the samples. 'labels' should be a numeric vector 0 / 1. 0 specifying the samples of, e.g., the control group and 1 specifying, e.g., the case group.
unlog	'TRUE' if the data have to be unlog before the foldchange calculation.

Value

A vector of length 'n genes' with the foldchange for each genes.

Author(s)

Nicolas Servant, Eleonore Gravier, Pierre Gestraud, Cecile Laurent, Caroline Paccard, Anne Biton, Jonas Mandel, Bernard Asselain, Emmanuel Barillot, Philippe Hupe

Examples

## load data
data(marty)

## Not run: 
## filtering data
marty <- expFilter(marty, threshold=3.5, graph=FALSE)

## End(Not run)

##Class label 0/1
marty.type.num <- ifelse(marty.type.cl=="Her2+",0,1)

## run folchange on 50 genes
fcOUT <- foldchange(marty[1:50,], marty.type.num)

EMA documentation built on March 26, 2020, 8:40 p.m.