In JoelleJee/DGOplot: DO and GO Enrichment Analyses Plotting

library(knitr)
opts_chunk$set(fig.align = "center", 
               out.width = "90%",
               fig.width = 6, fig.height = 5.5,
               dev.args=list(pointsize=10),
               par = TRUE, # needed for setting hook 
               collapse = TRUE, # collapse input & ouput code in chunks
               warning = FALSE)

knit_hooks$set(par = function(before, options, envir)
  { if(before && options$fig.show != "none") 
       par(family = "sans", mar=c(4.1,4.1,1.1,1.1), mgp=c(3,1,0), tcl=-0.5)
})
set.seed(1) # for exact reproducibility

Introduction

DGOplot is a contributed R package for performing Disease Ontology (DO) and Gene Ontology (GO) enrichment analyses and plotting the results. It provide a functions for combined DO and GO enrichment analyses on high-throughput Human Gene data based on R package DOSE and clusterProfiler. This package depends on clusterProfiler and DOSE for enrichment analyses. Also included are functions that allows visualization of such enrichment results into a barplot and to a gene association network.

This document gives a quick tour of DGOplot (version r packageVersion("DGOplot")) functionalities. It was written in R Markdown, using the knitr package for production and mclust vignette format.

See help(package="DGOplot") for further details and references provided by citation("DGOplot"). We will be using the dataset geneLIst provided by the DOSE package to demonstrate the functionalities of DOSE. geneList is named vector of gene expression levels and gene entrez id.

library(DGOplot)

DO and GO Enrichment Analysis

library(DOSE)
data(geneList)
head(geneList)
gene <- names(geneList)[abs(geneList) > 2]
head(geneList)
DGOResult <- enrichDGO(gene, 
                       universe=names(geneList),
                       pvalueCutoff = 0.5)
head(DGOResult$GO@result)
head(DGOResult$DO@result)

Barplot

DGObarplot(DGOResult)
DGObarplot(DGOResult, showCategory = 4)
DGObarplot(DGOResult, 
           showCategory = 4,
           DOcol = c("yellow", "green"),
           GOcol = c("blue", "purple"))

Warnings are generated when the available number of groups for each ontology enrichment results are smaller than the showCategory value given.

Gene Association Network

Visualization of gene association to the ontology groups. Layout is adapted from ahmohamed on gitHub. Color of the nodes and edges can be changed; see

DGOnetplot(DGOResult)
DGOnetplot(DGOResult, showCategory = 5)
DGOnetplot(DGOResult, 
           cluster.strength = 5,
           pAdjustCutoff = 0.05)

Warnings are generated when the available number of groups for each ontology enrichment results are smaller than the showCategory value given. The color of the ontology nodes are produced by RColorBrewer::brewer.pal(numGroups, "PuOr").

References

Scrucca L., Fop M., Murphy T. B. and Raftery A. E. (2016) mclust 5: clustering, classification and density estimation using Gaussian finite mixture models, The R Journal, 8/1, pp. 205-233. https://journal.r-project.org/archive/2016/RJ-2016-021/RJ-2016-021.pdf

Yu G, Wang L, Yan G, He Q (2015). “DOSE: an R/Bioconductor package for Disease Ontology Semantic and Enrichment analysis.” Bioinformatics, 31(4), 608-609. doi: 10.1093/bioinformatics/btu684, http://bioinformatics.oxfordjournals.org/content/31/4/608.

Yu G, Wang L, Han Y, He Q (2012). “clusterProfiler: an R package for comparing biological themes among gene clusters.” OMICS: A Journal of Integrative Biology, 16(5), 284-287. doi: 10.1089/omi.2011.0118.

ahmohamed (2015, Mar 3). "How to spread out community graph made by using igraph package in R." In Stack Overflow. Retrieved 23:37, December 1, 2019, from https://stackoverflow.com/questions/28715736/how-to-spread-out-community-graph-made-by-using-igraph-package-in-r/28722680#28722680.