clEnrich | R Documentation |
Gene set enrichment for clusters sourced from coExp function. the enrichment score are based on -log2(p) with p from hyper-geometric test.
clEnrich(
genecl_obj,
annofile = NULL,
sampleLabel = NULL,
TermFreq = 0,
ncore = 1
)
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 |
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)
a list containing the enrichment score for each clustering methods and cluster numbers included in the genecl_obj
Gene sets are from
1. http://www.broadinstitute.org/gsea/msigdb/index.jsp
2. http://amp.pharm.mssm.edu/Enrichr/
#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)
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