GOplot

Dependency of R packages

• library(dplyr)
• library(tibble)
• library(readr)
• library(ggplot2)
• library(ggdendro)
• library(rlang)
• library(msigdb) # https://github.com/mw201608/msigdb
• library(multiplot) # https://github.com/ericaenjoy3/multiplot
• library(RColorBrewer)
• library(methods)
• library(stats)
• library(grDevices)

Installation

devtools::install_github("ericaenjoy3/GOplot")

Load the package

library(GOplot)

Use selDB function to create/initialize a new gene set (gset) object

Current available database:

• "C1.CYTO": positional gene sets;
• "C2.CGP": chemical and genetic perturbations;
• "C2.CP": Canonical pathways (including BioCarta, KEGG and Reactome gene sets);
• "C3.MIR": microRNA targets;
• "C3.TFT": transcription factor targets;
• "C4.CGN": cancer gene neighborhoods;
• "C4.CM": cancer modules;
• "C5.BP": GO biological process;
• "C5.CC": GO cellular component;
• "C5.MF": GO molecular function;
• "C6.ONCOGENE": oncogenic signatures;
• "C7.IMMUNE": immunologic signatures.

For example, to load canonical pathways

gset.obj <- selDB(major="C2.CP", minor="Reactome", type="symbols", species="mouse")

or to load gene ontology biological process

gset.obj <- selDB(major="C5.BP", minor=NA, type="symbols", species="mouse")

Initialize a gclus object (with colnames of gene and clus)

For example, prepare gene signatures to be tested

signatures=data.frame(gene = as.character(c("Nanog","Rpl3","Rpl4","Mbl2","Ubr1","Herc2","Asb4","Rnf123","Klf4","Uba5")),
	clus = factor(rep(c('Group1','Group2'),c(6,4))))
gclus.obj <- new("gclus", tbl=tibble:::as_tibble(signatures))

Perform GO analysis

res.list <- GO(gclus.obj, gset.obj, filterPADJ=FALSE, filterOR=TRUE)
go_set.obj <- res.list$go_set.obj
go_res.obj <- res.list$go_res.obj

Output GO results to file

• nms is the file prefix for output
• output file named as [nms]_GOres.txt

write_GO(go_set.obj, go_res.obj, nms='test')

Plot GO results to png

• output file named as [nms]_GOhclus[clusname].png

simi(go_set.obj, go_res.obj, nms='test')