GO term enrichment using goseq
get_enriched_go.RdA wrapper function around goseq to perform
GO term enrichment analysis. See the goseq documentation
for details. pwf can be made using nullp.
Over/underrepresented p-values are automatically
adjusted using method = "BH". If gene2cat is not provided then this
function will default to using the Homo sapiens genome hg19 and will
expect Ensembl gene IDs to have been used to construct the pwf input.
Usage
get_enriched_go(
pwf,
gene2cat = NULL,
...,
shorten_term = TRUE,
shorten_lims = c(1L, 30L),
filter_no_DE = TRUE
)Arguments
- pwf
data.framewith 3 columns (DEgenes= logical,bias.data= numeric/integer,pwf= numeric) and row names (usually UniProt accessions, Ensembl gene IDs or similar). Typically constructed usingnullp.- gene2cat
data.framewith 2 columns containing the mapping between genes (usually UniProt accessions, Ensembl gene IDs or similar) and GO terms. Alternatively, anamed listwhere the names are genes and each entry is acharacter vectorof GO terms.- ...
Other arguments to be passed to
goseq.- shorten_term
logical. Should an extra column with a substring of the output GO terms be added to the output data.frame? Default isTRUE.- shorten_lims
integer vectorof length 2. The start and stop coordinates of the substring.- filter_no_DE
logical. Should terms without any features in the foreground be removed?