complexStatus: Complex Status
In PCpheno: Phenotypes and cellular organizational units

Description Usage Arguments Details Value Author(s) Examples

Categorize the complex whether or not a complex is composed of a significant number of genes involved in a particular phenotype than expected by chance.

1	complexStatus(data, phenotype, interactome, threshold=0.05)

`data`	Output from CoHyperG test
`phenotype`	List of gene names inducing an observed phenotype, e.g., list of essential gene names (see package SLGI)
`interactome`	A binary matrix composed of genes (rows) and biological complexes (columns) (see package ScISI)
`threshold`	pvalue threshold (default 0.05)

We form four distinct categories from A to D to characterize how a complex might be involved in a particular phenotype (according to the number of genes it contains and that are involved in a particular phenotype - see also hyperGTest function)

The returned value is a list with components:

`A`	"interesting" complexes, complexes with a significant number of interesting genes, i.e., genes that participate to a particular phenotype (at a given p-values threshold)
`B`	complexes with a NON significant number of interesting genes BUT that SHARE genes with complexes from the A status
`C`	complexes with a NON significant number of interesting genes AND that DON'T SHARE interesting genes with complexes from cat A
`D`	complexes WITHOUT interesting genes, i.e. the one involved in the studied phenotype

N. LeMeur

data(ScISI)
data(essglist)
essential <- names(essglist)

CoparamsESS <- new("CoHyperGParams",
                   geneIds=essential, 
                   universeGeneIds=rownames(ScISI),
                   annotation="org.Sc.sgd.db",
                   categoryName="ScISI",
                   pvalueCutoff=0.01,
                   testDirection="over")

sign<- hyperGTest(CoparamsESS)
test05 <-complexStatus(data=sign, phenotype=essential,
interactome=ScISI, threshold=0.05)