FastKEGG: KEGG analysis via clusterProfiler package

In shijianasdf/BasicBioinformaticsAnalysisFromZhongShan: Launch Usual Clinical tool for Kind Yield

Description

FastKEGG is a fast way to do KEGG analysis via series funtion of clusterProfiler package and automatically save related files or plots

Usage

FastKEGG(genes, geneList, default.universe = F, organism = "hsa",
  pvalueCutoff = list(enrichKEGG = 0.05, enrichMKEGG = 0.05),
  qvalueCutoff = 0.1, cnet.showCategory = 10, verbose = T,
  save.path = "KEGG", names = "love")

Arguments

genes	a character of gene id.
geneList	a numeric with id names.For example,logFoldChang with ENSEMBL id names.Note that the names of geneList must be the same type of genes
default.universe	whether to use default universe.If default.universe = F,the background genes would be provide by geneList
organism	Species.Default is "hsa"(homo species).
pvalueCutoff	a list of pvalue adjust method for enrichKEGG and enrichMKEGG
qvalueCutoff	cutoff of q value
cnet.showCategory	the number of showed cluster at cnetplot
verbose	LuckyVerbose gseplot running message or not
save.path	the sub path of saved files
names	the main path and part names of saved files

Examples

Plus.library("clusterProfiler")
data(geneList, package='DOSE')
genes <- names(geneList);
genes <- genes[1:2000]
kegg <- FastKEGG(genes = genes,
                organism = 'hsa',
                pvalueCutoff = 0.05,
                qvalueCutoff = 0.2,
                save.path = "KEGG",
                names = "love")
View(kegg)

shijianasdf/BasicBioinformaticsAnalysisFromZhongShan documentation built on Jan. 3, 2020, 10:08 p.m.