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#All classes used in the package
#class to store information about a pathway and associated genes
setClass("pathwayresult",
representation( pathwayuri="character",
label="character",
numgenes="numeric",
genes="vector"))
#class used to store gene references, including the URI, name, ID, species and experimental factors associated with the gene
generef <- setRefClass("generef",
fields = list( geneuri = "character",
genelabel = "character",
geneensemblid = "character",
species = "character",
exfactoruris="vector"),
methods = list(
setgeneuri = function(value) {
geneuri <<- value
invisible(value)
},
getgeneuri = function() {
return(geneuri)
},
setgenelabel = function(value) {
genelabel <<- value
invisible(value)
},
getgenelabel = function() {
return(genelabel)
},
setensemblid = function(value) {
geneuri <<- value
invisible(value)
},
getensemblid = function() {
return(geneuri)
},
setspecies = function(value) {
species <<- value
invisible(value)
},
getspecies = function() {
return(species)
},
getexfactoruris = function() {
return(exfactoruris)
},
show = function() {
message("An object of class generef used to store gene reference objects")
message("Field values")
message("geneuri: ", geneuri)
message("genelabel: ", genelabel)
message("geneensemblid: ", geneensemblid)
message("species: ", species)
message("exfactoruris (URI identifiers for experimental factors associated with this gene): ", exfactoruris)
},
#function to merge a passed parameter with the existing set of genes stored in this object
mergeexfactoruris = function(value){
if(!is.null(value)){
exfactoruris <<-unique(c(exfactoruris, value))
}
}
))
#the factor background class used in enrichment to represent an experimental factor and any associated genes for that
#factor. also stores info on super and subclasses of this factor
factorbackground <- setRefClass("factorbackground",
fields = list( uri = "character",
label = "character",
species = "character",
geneuris="vector",
numgenesexpressed="integer",
numgenesnotexpressed="integer",
subclasses="vector",
superclasses="vector"),
methods = list(
seturi = function(value) {
uri <<- value
invisible(value)
},
geturi = function() {
return(uri)
},
setlabel = function(value) {
label <<- value
invisible(value)
},
getlabel = function() {
return(label)
},
setspecies = function(value) {
species <<- value
invisible(value)
},
getspecies = function() {
return(species)
},
setgeneuris = function(value) {
geneuris <<- value
invisible(value)
},
getgeneuris = function() {
return(geneuris)
},
setnumgenesexpressed = function(value) {
numgenesexpressed <<- value
invisible(value)
},
getnumgenesexpressed = function() {
return(numgenesexpressed)
},
setnumgenesnotexpressed = function(value) {
numgenesnotexpressed <<- value
invisible(value)
},
getnumgenesnotexpressed = function() {
return(numgenesnotexpressed)
},
setsubclasses = function(value) {
subclasses <<- value
invisible(value)
},
getsubclasses = function() {
return(subclasses)
},
setsuperclasses = function(value) {
superclasses <<- value
invisible(value)
},
getsuperclasses = function() {
return(superclasses)
},
show = function() {
message("An object of class factorbackground used to store an experimental factor and any gene associated with them")
message("Field values")
message("uri (identifier for the factor): ", uri)
message("label (human readable label for the factor): ", label)
message("species (the species of the genes associated with the factor): ", species)
message("geneuris (the URI identifiers of the genes associated with the factor): ", geneuris)
message("numgenesexpressed (the total number of genes differetially expressed and associated with the factor): ", numgenesexpressed)
message("numgenesnotexpressed (the total number of genes not differetially expressed and associated with the factor): ", numgenesnotexpressed)
message("subclasses (ontology subclasses for this factor): ", subclasses)
message("superclasses (ontology superclasses for this factor): ", superclasses)
},
#function to merge a passed parameter with the existing set of genes stored in this object
mergegeneuris = function(value){
if(!is.null(value)){
geneuris <<-unique(c(geneuris, value))
}
}
))
#class to store enrichemt results, including the uri of the factor plus information on the statistics for enrichment
#such as p.value and the genes enriched for this factor
setClass("enrichmentresult",
representation( factoruri="character",
label="character",
p.value="numeric",
estimate="numeric",
alternative="character",
null.value="numeric",
method="character",
enrichedgenes="vector"))
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