Coutput-class | R Documentation |
Coutput
is an S4 class to store output by
dcRWRpipeline
.
Class Coutput
ratio
A symmetrix matrix, containing ratio
zscore
A symmetrix matrix, containing z-scores
pvalue
A symmetrix matrix, containing p-values
adjp
A symmetrix matrix, containing adjusted p-values
cnetwork
An object of S4 class Cnetwork
,
storing contact network.
An object of this class can be created via: new("Coutput", ratio,
zscore, pvalue, adjp, cnetwork)
Class-specific methods:
ratio()
: retrieve the slot 'ratio' in the object
zscore()
: retrieve the slot 'zscore' in the object
pvalue()
: retrieve the slot 'pvalue' in the object
adjp()
: retrieve the slot 'adjp' in the object
cnetwork()
: retrieve the slot 'cnetwork' in the object
write()
: write the object into a local file
Standard generic methods:
str()
: compact display of the content in the object
show()
: abbreviated display of the object
Ways to access information on this class:
showClass("Coutput")
: show the class definition
showMethods(classes="Coutput")
: show the method
definition upon this class
getSlots("Coutput")
: get the name and class of each slot
in this class
slotNames("Coutput")
: get the name of each slot in this
class
selectMethod(f, signature="Coutput")
: retrieve the
definition code for the method 'f' defined in this class
Coutput-method
## Not run: # 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) ## End(Not run)
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