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Performing quick ORA analysis

easytopGO.Rd

A convenience function to quickly perform GO Term Enrichment analysis using TopGO.The results then can be plotted using easyGOPlot

Usage

easytopGO(
  geneID,
  bkggset = "",
  gaf = "",
  useBiomart = TRUE,
  useGAF = FALSE,
  mart = "protists_mart",
  gset = "pfalciparum_eg_gene",
  algo = "weight01",
  stats = "ks",
  category = "BP",
  fdr = FALSE,
  correction = "BY"
)

Arguments

geneID

A vector of named p-values. The names should be gene IDs.

bkggset

A character vector of gene IDs that should be used as background.

gaf

A URL or path to the .gaf file obtained from PlasmoDB should you choose not to use biomaRt. When using this argument, set useBiomart=FALSE and useGAF=TRUE.

useBiomart

Logical To enable usage of BiomaRt to fetch GO terms. Default: TRUE.

useGAF

Logical To enable usage of custom .gaf file to fetch GO terms. Default: FALSE

mart

Argument to specify the mart for BiomaRt functions. Default: "protists_mart".

gset

Argument to specify the geneset to be used by BiomaRt functions. Default: "pfalciparum_eg_gene"

algo

Argument to specify which algorithm to be used for enrichment by topGO. For possible options use topGO::whichAlgorithms()

stats

Argument to specify the statistical test to be used for enrichment by topGO. For possible values use topGO::whichTests(). Default: "ks".

category

Specify the category of Over-representation analysis such as "BP" for Biological Process, "MF" for Molecular Function and "CC" for Cellular Component Enrichment.

fdr

logical. Perform multiple testing correction testing. Default (FALSE)

correction

Method to be used to calculate adjusted p-value. Possible values: ""holm", "hochberg", "hommel", "bonferroni", "BH", "BY","fdr". Read section 6.2 in topGO documentation before performing correction. Correction when using elim and weight is usually not recommended.

Value

A dataframe of enriched terms with GO description and genes filteres by uncorrected p-values.

Examples

if (FALSE) { # \dontrun{
## making gene list from DESEq2
geneList <- subset(res, regulate=="Up") %>% .$padj
names(geneList) <- subset(res, regulate=="Up") %>% .$Geneid

## background genes will be the genes tested for differential expression
background.gset <- res$Geneid
baseurl <- "https://plasmodb.org/common/downloads/Current_Release/"
url<-paste0(baseurl,"Pfalciparum3D7/gaf/PlasmoDB-68_Pfalciparum3D7_GO.gaf.gz")
gores<-easytopGO(geneID = geneList,useGAF = TRUE,useBiomart = FALSE,gaf=url,
bkggset = background.gset, category = "BP", stats = "ks")
} # }