plot2D {RDAVIDWebService} | R Documentation |
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.
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
{ ##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) }