README.md

GOplot

Dependency of R packages

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

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

Plot GO results to png

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


ericaenjoy3/GOplot documentation built on May 6, 2019, 9:50 p.m.