clEnrich: Gene set enrichment for clusters

View source: R/clEnrich.R

clEnrichR Documentation

Gene set enrichment for clusters

Description

Gene set enrichment for clusters sourced from coExp function. the enrichment score are based on -log2(p) with p from hyper-geometric test.

Usage

clEnrich(
  genecl_obj,
  annofile = NULL,
  sampleLabel = NULL,
  TermFreq = 0,
  ncore = 1
)

Arguments

genecl_obj

a genecl object

annofile

gene set annotation file

sampleLabel

sameple Label. Do make the label of interest located after the control label in the order of factor. See details.

TermFreq

a value from [0,1) to filter low-frequence gene sets

ncore

the number of cores used

Details

sampleLable: Use factor(c("Normal", "Cancer", "Normal"), levels=c("Normal", "Cancer")), instead of factor(c("Normal", "Cancer","Normal")). This parameter will affect the direction of gene regulation in cogena.

Gene sets availiable (See vignette for more):

  • c2.cp.kegg.v7.01.symbols.gmt.xz (From Msigdb)

  • c2.cp.reactome.v7.01.symbols.gmt.xz (From Msigdb)

  • c5.bp.v7.01.symbols.gmt.xz (From Msigdb)

Value

a list containing the enrichment score for each clustering methods and cluster numbers included in the genecl_obj

Source

Gene sets are from

1. http://www.broadinstitute.org/gsea/msigdb/index.jsp

2. http://amp.pharm.mssm.edu/Enrichr/

Examples


#annotaion
annoGMT <- "c2.cp.kegg.v7.01.symbols.gmt.xz"
annofile <- system.file("extdata", annoGMT, package="cogena")

utils::data(Psoriasis)
clMethods <- c("hierarchical","kmeans","diana","fanny","som","model","sota","pam","clara","agnes")
genecl_result <- coExp(DEexprs, nClust=2:3, clMethods=c("hierarchical","kmeans"), 
    metric="correlation", method="complete", ncore=2, verbose=TRUE)

clen_res <- clEnrich(genecl_result, annofile=annofile, sampleLabel=sampleLabel)
    

zhilongjia/cogena documentation built on Nov. 21, 2023, 1:34 a.m.