topReviGO: Chain topGO and REViGO analyses to produce treemaps
In achateigner/topReviGO: Chain topGO and REViGO analyses to produce treemaps

Description Usage Arguments Details Value Examples

This package takes a list of genes, a map file with the correspondance between gene name and GO annotation and a prefix for the output. It will then do a topGO analysis and send the results to the REViGO (http://revigo.irb.hr/) website, to summarize the list of GO and produce a treemap.

1 2	topReviGO(geneList, prefix, mapFile, ontology = "BP", mapOrDb = "map", p = 0.01)

`geneList`	The gene list must be a csv file without column name, each line consisting of the gene name and a 1 or 0, separated by a ",". The 1 or 0 corresponds to the fact that the gene is respectively selected or not. What I mean by that is that the gene has previously been recognized by the user as interesting, like belonging to a cluster, or selected by any other way. It corresponds to the "Predefined list of interesting genes" from the topGO vignette (http://www.bioconductor.org/packages/release/bioc/vignettes/topGO/inst/doc/topGO.pdf). If you don't have a predefined list, please do the previous steps of the topGO vignette (before 4.4).
`prefix`	A prefix for the outputs.
`mapFile`	A file containing the correspondance between the gene name and a GO name, 1 per line, in the format : GeneName<tabulation>GOName It can also be a Db name, thus one needs to change the option mapOrDb.
`ontology`	"BP", "CC" or "MF" for Biological Process, Cellular Component or Molecular Function, this is the GO categories outputted by REViGO.
`mapOrDb`	map if a map file is used, db if a database name is provided.
`p`	the p-value for the weight Fisher test to accept the GO. The Ficher test based on weights takes multiple testing into account directly without further need to apply a fdr or bonferroni correction.

The goal is from a list of genes and the corresponding GO map, to be able to produce an enriched list of GO annotations and a treemap to easily visualize. By default, the biological process is outputted, but it can also be the Cellular Component or the Molecular Function. One can use a installed db or a map file.

A csv file containing the enriched GO terms and a treemap pdf file containing the image.

library(hgu133a.db)
selGenes <- sample(ls(hgu133aGO), 50)
allGenes <-  factor(as.integer(ls(hgu133aGO) %in% selGenes))
names(allGenes) <- ls(hgu133aGO)
topReviGO(allGenes, "toto", "hgu133a", mapOrDb = "db", p = 0.01)