cogena_package {cogena} | R Documentation |
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.
https://github.com/zhilongjia/cogena
## 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.v5.0.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