viewEnrichMap: Plot a figure of the enrichment map for GSEA or...

In HTSanalyzeR: Gene set over-representation, enrichment and network analyses for high-throughput screens

Description

This is a generic function.

When implemented as the S4 method for objects of class GSCA, this function will plot an enrichment map for GSEA or Hypergeometric test results.

To use this function for objects of class GSCA:

viewEnrichMap(object, resultName="GSEA.results", gscs, ntop=NULL, allSig=TRUE, gsNameType="id", displayEdgeLabel=TRUE, layout= "layout.fruchterman.reingold")

Usage

viewEnrichMap(object, ...)

Arguments

object	an object. When this function is implemented as the S4 method of class GSCA, this argument is an object of class GSCA.
...	other arguments. (see below for the arguments supported by the method of class GSCA)

resultName:

a single character value: 'HyperGeo.results' or 'GSEA.results'

gscs:

a character vector specifying the names of gene set collections of which the top significant gene sets will be plotted

ntop:

a single integer or numeric value specifying how many gene sets of top significance will be plotted.

allSig:

a single logical value. If 'TRUE', all significant gene sets (GSEA adjusted p-value < 'pValueCutoff' of slot 'para') will be used; otherwise, only top 'ntop' gene sets will be used.

gsNameType:

a single character value specifying the type of the gene set names that will be displayed as the names of nodes in the enrichment map. The type of the gene set names should be one of the following: "id", "term" or "none".

displayEdgeLabel:

a single logical value specifying whether or not to display the labels of the edges in the enrichment map

layout:

a single character value specifying the layout of the enrichment map. (see help(layout) of the package igraph)

plot:

a single logical value. If 'TRUE', the enrichment map will be plotted; otherwise the function only returns the igraph of enrichment map.

Details

The idea of this function is similar to the PLoS one paper by Merico et al.

An enrichment map is a network to help better visualize and interpret the GSEA or Hypergeometric test results. In an enrichment map, the nodes represent gene sets and the edges denote the Jaccard similarity coefficient between two gene sets. Node colors are scaled according to the adjusted p-values (the darker the more significant). For GSEA, nodes are colored by the sign of the enrichment scores (red:+, blue: -). The size of nodes illustrates the size of gene sets, while the width of edges denotes the Jaccard coefficient.

Value

an object of igraph with all attributes about the enrichement map

Author(s)

Xin Wang [e-mail]

References

Merico, D. et al, Enrichment Map: A Network-Based Method for Gene-Set Enrichment Visualization and Interpretation, PloS one, 2010, e13984

See Also

plotEnrichMap

Examples

## Not run: 
library(org.Dm.eg.db)
library(KEGG.db)
##load data for enrichment analyses
data("KcViab_GSCA")
##plot and save the enrichment map
viewEnrichMap(KcViab_GSCA, gscs=c("GO_MF"), allSig=TRUE, ntop=NULL, gsNameType="id", 
displayEdgeLabel=FALSE,layout="layout.fruchterman.reingold")
##append Gene set terms to results
KcViab_GSCA<-appendGSTerms(KcViab_GSCA, goGSCs=c("GO_BP","GO_MF","GO_CC"), 
keggGSCs=c("PW_KEGG"))
viewEnrichMap(KcViab_GSCA, gscs=c("GO_MF"), allSig=TRUE, ntop=NULL, gsNameType="term", 
displayEdgeLabel=FALSE,layout="layout.fruchterman.reingold")

## End(Not run)

HTSanalyzeR documentation built on Oct. 31, 2019, 7:10 a.m.