Description Usage Arguments Value Author(s) See Also Examples
plot2D uses a 2D tile ggplot to explore biological
relationships between two variables such as annotation
category and genes, for Functional Annotation Chart/Table
or Term cluster results. For Gene cluster, the cluster
number vs genes membership is plotted.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | plot2D(object,...)
## S4 method for signature 'DAVIDResult'
plot2D(object, dataFrame)
## S4 method for signature 'DAVIDFunctionalAnnotationChart'
plot2D(object,color=c("FALSE"="black",
"TRUE"="green"))
## S4 method for signature 'DAVIDGeneCluster'
plot2D(object,color=c("FALSE"="black","TRUE"="green"),names=FALSE)
## S4 method for signature 'DAVIDTermCluster'
plot2D(object,number=1,color=c("FALSE"="black","TRUE"=
"green"))
## S4 method for signature 'DAVIDFunctionalAnnotationTable'
plot2D(object,
category, id, names.genes=FALSE,
names.category=FALSE,color=c("FALSE"="black","TRUE"="green"))
|
object |
DAVIDResult heirs (DAVIDFunctionalAnnotationChart/Table or DAVIDGeneCluster/TermCluster) |
dataFrame |
data.frame with three columns (x, y and fill) to be used in ggplot. X(Y) is a character/factor with the X(Y)-axis labels and "fill" is a the color to be used for x-y labels. |
color |
named character vector to indicate tile color. Default value is c("FALSE"="black", "TRUE"="green"). |
names |
should gene names be plotted? Default value is FALSE, i.e, use ids. |
number |
integer to indicate which cluster to plot. Default value is 1. |
category |
character vector to select the main annotation categories. By default is missing in order to use all the available ones. |
id |
character vector to indicate which gene ids to use. By default is missing in order to use all the available ones. |
names.genes,names.category |
Should genes and/or category names used? Default value is FALSE, i.e., use both ids. |
... |
Additional parameters for heirs functions. |
a ggplot object if the object is not empty.
Cristobal Fresno and Elmer A Fernandez
Other DAVIDFunctionalAnnotationChart:
DAVIDFunctionalAnnotationChart,
DAVIDFunctionalAnnotationChart,
DAVIDFunctionalAnnotationChart,
DAVIDFunctionalAnnotationChart-class,
DAVIDFunctionalAnnotationTable,
DAVIDFunctionalAnnotationTable,
DAVIDFunctionalAnnotationTable,
DAVIDGODag, DAVIDGODag,
DAVIDGeneCluster,
DAVIDGeneCluster, DAVIDGenes,
DAVIDGenes, DAVIDGenes,
DAVIDTermCluster,
DAVIDTermCluster, as,
as, as,
categories, categories,
categories, ids,
ids, ids, ids,
ids, initialize,
initialize, initialize,
initialize, initialize,
initialize, initialize
Other DAVIDFunctionalAnnotationTable:
DAVIDFunctionalAnnotationChart,
DAVIDFunctionalAnnotationChart,
DAVIDFunctionalAnnotationChart,
DAVIDFunctionalAnnotationTable,
DAVIDFunctionalAnnotationTable,
DAVIDFunctionalAnnotationTable,
DAVIDFunctionalAnnotationTable-class,
DAVIDGODag, DAVIDGODag,
DAVIDGeneCluster,
DAVIDGeneCluster, DAVIDGenes,
DAVIDGenes, DAVIDGenes,
DAVIDTermCluster,
DAVIDTermCluster, as,
as, as,
categories, categories,
categories, dictionary,
dictionary, genes,
genes, genes,
genes, initialize,
initialize, initialize,
initialize, initialize,
initialize, initialize,
membership, membership,
subset, subset
Other DAVIDGeneCluster:
DAVIDFunctionalAnnotationChart,
DAVIDFunctionalAnnotationChart,
DAVIDFunctionalAnnotationChart,
DAVIDFunctionalAnnotationTable,
DAVIDFunctionalAnnotationTable,
DAVIDFunctionalAnnotationTable,
DAVIDGODag, DAVIDGODag,
DAVIDGeneCluster,
DAVIDGeneCluster,
DAVIDGeneCluster-class,
DAVIDGenes, DAVIDGenes,
DAVIDGenes, DAVIDTermCluster,
DAVIDTermCluster, as,
as, as, genes,
genes, genes,
genes, ids,
ids, ids, ids,
ids, initialize,
initialize, initialize,
initialize, initialize,
initialize, initialize
Other DAVIDResult: DAVIDResult-class,
type, type
Other DAVIDTermCluster:
DAVIDFunctionalAnnotationChart,
DAVIDFunctionalAnnotationChart,
DAVIDFunctionalAnnotationChart,
DAVIDFunctionalAnnotationTable,
DAVIDFunctionalAnnotationTable,
DAVIDFunctionalAnnotationTable,
DAVIDGODag, DAVIDGODag,
DAVIDGeneCluster,
DAVIDGeneCluster, DAVIDGenes,
DAVIDGenes, DAVIDGenes,
DAVIDTermCluster,
DAVIDTermCluster,
DAVIDTermCluster-class, as,
as, as, ids,
ids, ids, ids,
ids, initialize,
initialize, initialize,
initialize, initialize,
initialize, initialize
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 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 | {
##DAVIDFunctionalAnnotationChart example:
##Load the Functional Annotation Chart file report for the input demo
##file 2, using data function. Just to keep it simple, for the first five
##terms present in funChart2 object, create a DAVIDFunctionalAnnotationChart
##object and plot a 2D tile matrix with the reported evidence (green) or not
##(black).
data(funChart2)
plot2D(DAVIDFunctionalAnnotationChart(funChart2[1:5, ]),
color=c("FALSE"="black", "TRUE"="green"))
##DAVIDFunctionalAnnotationTable example
##Load the Functional Annotation Table file report for the input demo
##file 1, using data function. Then, create a DAVIDFunctionalAnnotationTable
##object using the loaded data.frame annotationTable1.
data(annotationTable1)
davidFunTable1<-DAVIDFunctionalAnnotationTable(annotationTable1)
##Plot the membership of only for the first six terms in this
##category, with only the genes of the first six terms with at least one
##evidence code.
##Category filtering...
categorySelection<-list(head(dictionary(davidFunTable1,
categories(davidFunTable1)[1])$ID))
names(categorySelection)<-categories(davidFunTable1)[1]
##Gene filter...
id<-membership(davidFunTable1, categories(davidFunTable1)[1])[,1:6]
id<-ids(genes(davidFunTable1))[rowSums(id)>0]
##Finally the membership tile plot
plot2D(davidFunTable1, category=categorySelection, id=id,
names.category=TRUE)
##DAVIDGeneCluster example:
##Load the Gene Functional Classification Tool file report for the
##input demo list 1 file to create a DAVIDGeneCluster object.
setwd(tempdir())
fileName<-system.file("files/geneClusterReport1.tab.tar.gz",
package="RDAVIDWebService")
untar(fileName)
davidGeneCluster1<-DAVIDGeneCluster(untar(fileName, list=TRUE))
##We can inspect a 2D tile membership plot, to visual inspect for
##overlapping of genes across the clusters. Or use an scaled version of gene
##names to see the association of gene cluster, e.g., cluster 3 is related to
##ATP genes.
plot2D(davidGeneCluster1)
plot2D(davidGeneCluster1,names=TRUE)+
theme(axis.text.y=element_text(size=rel(0.9)))
##DAVIDTermCluster example:
##Load the Gene Functional Classification Tool file report for the
##input demo file 2 to create a DAVIDGeneCluster object.
setwd(tempdir())
fileName<-system.file("files/termClusterReport2.tab.tar.gz",
package="RDAVIDWebService")
untar(fileName)
davidTermCluster2<-DAVIDTermCluster(untar(fileName, list=TRUE))
##Finally, we can inspect a 2D tile membership plot, to visual inspect for
##overlapping of genes across the term members of the selected cluster,
##e.g., the first cluster .
plot2D(davidTermCluster2, number=1)
}
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