cogena_package: Co-expressed gene set enrichment analysis

In cogena: co-expressed gene-set enrichment analysis

Description

To discovery smaller scale, but highly correlated cellular events that may be of great biological relevance, co-expressed gene set enrichment analysis, cogena, clusters gene expression profiles (coExp) and then make enrichment analysis for each clusters (clEnrich) based on hyper-geometric test. The heatmapCluster and heatmapPEI can visualise the results. See vignette for the detailed workflow.

Source

https://github.com/zhilongjia/cogena

Examples

## A quick start

# Loading the examplar dataseat
data(Psoriasis)

# Clustering the gene expression profiling
clMethods <- c("hierarchical","kmeans","diana","fanny","som","model","sota","pam","clara","agnes")
genecl_result <- coExp(DEexprs, nClust=5:6, clMethods=clMethods, 
    metric="correlation", method="complete", ncore=2, verbose=TRUE)

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

# Enrichment analysis for clusters
clen_res <- clEnrich(genecl_result, annofile=annofile, sampleLabel=sampleLabel)

summary(clen_res)


# Visualisation
heatmapCluster(clen_res, "hierarchical", "6")
heatmapPEI(clen_res, "hierarchical", "6", printGS=FALSE)

# Obtain genes in a certain cluster
head(geneInCluster(clen_res, "hierarchical", "6", "2"))

## The end

cogena documentation built on Nov. 8, 2020, 6:54 p.m.