Extract significant enrichment terms base on giving threshold

get_ORA_result filter the enrichment result from test_ORA though certain threshold.

Usage

get_ORA_result(
  ORA_enrichment,
  ont = NULL,
  pvalueCutoff = 0.05,
  qvalueCutoff = 0.2,
  simplify = FALSE,
  simplify.cutoff = 0.7,
  simplify.measure = c("Wang", "Resnik", "Lin", "Rel", "Jiang"),
  simplify.semData = NULL,
  return_table = F
)

Arguments

ont

One of "ALL", "BP", "MF", "CC"

pvalueCutoff

Numeric(1), the p.value cutoff on enrichment result

qvalueCutoff

Numeric(1), the qvalue cutoff on enrichment tests

simplify

Logical(1), if simplify GO terms by simplify

simplify.cutoff

Numeric(1), the cutoff value transmitted to simplify

return_table

Logical(1), if true return a enrichResult or a result table

reat

The output from test_ORA

Value

A enrichResult/compareClusterResult of significant enrichment, or a result table of the significant enrichment if return_table is TRUE.

Examples

if (FALSE) {
# Load example
data(Silicosis_pg)
data <- Silicosis_pg
data_unique <- make_unique(data, "Gene.names", "Protein.IDs", delim = ";")

# Differential test
ecols <- grep("LFQ.", colnames(data_unique))
se <- make_se_parse(data_unique, ecols,mode = "delim")
filt <- filter_se(se, thr = 0, fraction = 0.4, filter_formula = ~ Reverse != "+" & Potential.contaminant!="+")
norm <- normalize_vsn(filt)
imputed <- impute(norm, fun = "MinProb", q = 0.05)
diff <- test_diff(imputed, type = "control", control  = c("PBS"), fdr.type = "Storey's qvalue")

res_ora <- test_ORA(dep, contrasts = "W4_vs_PBS", species = "Mouse",type = "GO")
res_ora2 <- get_ORA_result(res_ora)
}