dna (version 2.1-2)

resultsClassTest-class: Class "resultsClassTest"

Description

Tests whether the connectivity scores for a set of important genes differ between two networks.

Objects from the Class

Objects can be created by calls of the form new("resultsClassTest", ...).

Slots

p.value:

Object of class "numeric"; the p-value for the significance test.

delta:

Object of class "numeric"; the test statistic for the significance test.

class.genes:

Object of class "character"; the list of important genes.

Methods

get.results

signature(object = "resultsClassTest"): returns the p-value, test statistic, and the class of genes for a test for differential connectivity of the class of genes.

show

signature(object = "resultsClassTest"): summarizes the test by outputing the class of important genes, the value of the test statistic, and its p-value.

References

Gill, R., Datta, S., and Datta, S. (2010) A statistical framework for differential network analysis from microarray data. BMC Bioinformatics, 11, 95.

Examples

# NOT RUN {
# small example illustrating test procedures
X1=rbind(
c(2.5,6.7,4.5,2.3,8.4,3.1),
c(1.2,0.7,4.0,9.1,6.6,7.1),
c(4.3,-1.2,7.5,3.8,1.0,9.3),
c(9.5,7.6,5.4,2.3,1.1,0.2))
colnames(X1)=paste("G",1:6,sep="")

X2=rbind(
c(4.5,2.4,6.8,5.6,4.5,1.2,4.5),
c(7.6,9.0,0.1,3.4,5.6,5.5,1.2),
c(8.3,4.5,7.0,1.2,4.3,3.7,6.8),
c(3.4,1.1,6.9,7.2,3.1,0.9,6.6),
c(3.4,2.2,1.3,5.5,9.8,6.7,0.6))
colnames(X2)=paste("G",8:2,sep="")

# perform a test for differential connectivity of all genes 
# with PLS connectivity scores and squared distances
## Not run: tcg=test.class.genes(X1,X2)
## Not run: results.tcg=get.results(tcg)
## Not run: results.tcg
# }