dna (version 2.1-2)

get.results-methods: Method for Function get.results

Description

get.results-methods

Methods

signature(object = "resultsIndTest")

returns the p-values and test statistics for tests for differential connectivity of individual genes.

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.

signature(object = "resultsModTest")

returns the p-value, test statistic, and the modules for each network for a test for overall modular structure.

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 individual genes 
# with PLS connectivity scores and squared distances
## Not run: tig=test.individual.genes(X1,X2)
## Not run: results.tig=get.results(tig)
## Not run: results.tig

# 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

# perform a test for modular structure using a minimum module size of 2
# and threshold of .5 with PLS connectivity scores
## Not run: test.modular.structure(X1,X2,min.module.size=2)
## Not run: results.tms=get.results(tms)
## Not run: results.tms
# }