find_enriched_go_terms: Find enriched GO terms
In NelleV/moanin: An R Package for Time Course RNASeq Data Analysis

Description Usage Arguments Details Value See Also Examples

Find enriched GO terms

Create the Gene to GO Term mapping

find_enriched_go_terms(
  assignments,
  gene_id_to_go,
  ontology = "BP",
  weighted = FALSE,
  node_size = 10
)

create_go_term_mapping(genes, gene_col = "refseq_mrna")

`assignments`	boolean named vector determining the gene subset to be tested for enrichment of GO terms. The names of the vector should be the gene names. Elements with TRUE will consist of the gene cluster.
`gene_id_to_go`	List giving the Gene ID to GO object required for topGO (see `topGOdata-class`). `create_go_term_mapping` can construct such a list from a data-frame.
`ontology`	string, optional, default: BP. specficies which ontology to use (passed to `ontology` argument in creating a new `topGOdata` object). Can be 'BP', 'CC', or 'NF'. See `topGOdata-class`.
`weighted`	boolean, optional, default: FALSE. Whether to use the weighted algorithm or not in `runTest`.
`node_size`	integer, optional, default: 10. Consider only GO terms with node_size number of genes, passed to `nodeSize` argument of `topGOdata-class`
`genes`	dataframe, with two required columns. The first gives the gene names, with column name by the argument `gene_col`. The other column must be named "go_id" and give the genes GO id. Genes will have multiple GO id that they map to, and each go mapping of a gene is a separate row. Thus genes will be in multiple rows of the input.
`gene_col`	the name of the column of the `genes` data frame that contains the correct gene reference. By default, is "refseq_mrna".

find_enriched_go_terms is a wrapper for running a GO enrichment analysis via the package topGO. This function creates a topGOdata-class object, runs the function runTest to test for enrichment using the statistic="fisher" option, and then runs GenTable. This function then does some post-processing of the results, returning only GO terms that satisfy:

BH adjusted p-values less than 0.05 using p.adjust
GO terms are enriched, i.e. the number of genes from the GO term found in the subset is greater than expected

Returns results in the format of GenTable.

create_go_term_mapping returns a list giving the gene to GO id in the format required by topGOdata-class.

create_go_term_mapping, find_enriched_pathway, GenTable, runTest, topGOdata-class, p.adjust

data(exampleData)
head(testGenesGO) #gives the mapping of genes to GO
geneId2Go <- create_go_term_mapping(testGenesGO)
#create fake assignment of genes to group based on TRUE/FALSE values
inGroup=rep(FALSE,nrow(testData))
inGroup[1:10]=TRUE
names(inGroup) <- row.names(testData)
find_enriched_go_terms(inGroup, geneId2Go)