padj_threshold: p.adjust threshold to determine whether a feature significant or not. p.adjust < padj_threshold, default: 0.05
logFC_threshold: logFC threshold to determine whether a feature significant or not. abs(logFC)>logFC_threshold, default: NULL
add_mini: add_mini when calculate the logFC. e.g (10+0.1)/(0+0.1), default 0.05*min(avg_abundance)
p.adjust.method: The method used for p-value adjustment (default: "BH").
type: "pathway" or "module" for default KOlist_file.
feature: one of "ko", "gene", "compound"
modulelist: NULL or customized modulelist dataframe, must contain "id","K_num","KOs","Description" columns. Take the KOlist as example, use custom_modulelist.
verbose: logical
Returns
data.frame
Examples
## use `fisher.test` from the `stats` package.data("reporter_score_res")fisher_res <- KO_fisher(reporter_score_res)
See Also
Other common_enrich: KO_enrich(), KO_gsa(), KO_gsea(), KO_gsva(), KO_padog(), KO_safe(), KO_sea(), plot_enrich_res()