Detection of differentially expressed genes.

Description

Detects differentially expressed genes between two distinct groups of samples.

Usage

1
deg(treatment, control, alpha = 0.05)

Arguments

treatment

Matrix of normalized expression levels in the first group. Rows represent genes, columns represent samples.

control

Matrix of normalized expression levels in the second group. Rows represent genes, columns represent samples.

alpha

Global significance level.

Details

The function controlls the FWER at the specified alpha-level.

Value

A vector with the row numbers of the genes detected as differentially expressed.

Author(s)

Klaus Jung

References

Jung K., Quast K., Gannoun A. and Urfer W. (2006) A renewed approach to the nonparametric analysis of replicated microarray experiments. Biometrical Journal, 48, 245-254.

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
X1 = matrix(rnorm(2000, 0, 1), 200, 10)
X2 = matrix(rnorm(2000, 0, 1), 200, 10)
index = sample(1:200, 5, replace=FALSE)
X2[index,] = X2[index,] + 5
D = deg(X1, X2)
PD = pdeg(X1, X2)
PDa = p.adjust(PD, method="bonferroni")
sort(index)
D
which(PDa<0.05)
which(PD<0.05)