Description Value Slots Creation Methods Access See Also Examples
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
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 | ## 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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