degenes (version 1.1)

pdeg: Detection of differentially expressed genes.

Description

Calculated gene-specific unadjusted p-values for the comparison of samples from two distinct groups.

Usage

pdeg(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.

Value

A vector with the gene-specific unadjusted p-values.

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

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)