# 1) load onto.GOMF (as 'Onto' object)
g <- dcRDataLoader('onto.GOMF')
# 2) load SCOP superfamilies annotated by GOMF (as 'Anno' object)
Anno <- dcRDataLoader('SCOP.sf2GOMF')
# 3) prepare for ontology appended with annotation information
dag <- dcDAGannotate(g, annotations=Anno, path.mode="shortest_paths",
verbose=TRUE)
# 4) calculate pair-wise semantic similarity between 10 randomly chosen domains
alldomains <- unique(unlist(nInfo(dag)$annotations))
domains <- sample(alldomains,10)
dnetwork <- dcDAGdomainSim(g=dag, domains=domains,
method.domain="BM.average", method.term="Resnik", parallel=FALSE,
verbose=TRUE)
dnetwork
# 5) estimate RWR dating based sample/term relationships
# define sets of seeds as data
# each seed with equal weight (i.e. all non-zero entries are '1')
data <- data.frame(aSeeds=c(1,0,1,0,1), bSeeds=c(0,0,1,0,1))
rownames(data) <- id(dnetwork)[1:5]
# calcualte their two contact graph
coutput <- dcRWRpipeline(data=data, g=dnetwork, parallel=FALSE)
coutput
# 6) write into the file 'Coutput.txt' in your local directory
write(coutput, file='Coutput.txt', saveBy="adjp")
# 7) retrieve several slots directly
ratio(coutput)
zscore(coutput)
pvalue(coutput)
adjp(coutput)
cnetwork(coutput)
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