dcGOR (version 1.0.6)

Coutput-class: Definition for S4 class Coutput

Description

Coutput is an S4 class to store output by dcRWRpipeline.

Value

Class Coutput

Slots

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.

Creation

An object of this class can be created via: new("Coutput", ratio, zscore, pvalue, adjp, cnetwork)

Methods

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

Access

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

See Also

Coutput-method

Examples

## 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)