## ---- echo = FALSE------------------------------------------------------------ library(knitr) knitr::opts_chunk$set( error = FALSE, tidy = FALSE, message = FALSE, warning = FALSE, fig.align = "center", dev = "jpeg" ) options(width = 80) ## ---- echo = FALSE, message = FALSE------------------------------------------- library(simplifyEnrichment) mat = readRDS(system.file("extdata", "random_GO_BP_sim_mat.rds", package = "simplifyEnrichment")) go_id = rownames(mat) ## ---- eval = FALSE------------------------------------------------------------ # library(simplifyEnrichment) # set.seed(888) # go_id = random_GO(500) ## ---- eval = FALSE------------------------------------------------------------ # mat = GO_similarity(go_id) ## ---- eval = FALSE------------------------------------------------------------ # GO_similarity(go_id, measure = "Wang") ## ---- fig.width = 7*1.2, fig.height = 4*1.2----------------------------------- df = simplifyGO(mat) ## ----------------------------------------------------------------------------- head(df) ## ----------------------------------------------------------------------------- sort(table(df$cluster)) ## ---- eval = FALSE------------------------------------------------------------ # split(df, df$cluster) ## ----------------------------------------------------------------------------- binary_cut(mat) ## ---- eval = FALSE------------------------------------------------------------ # cluster_terms(mat, method = "binary_cut") ## ---- fig.width = 10, fig.height = 7------------------------------------------ compare_clustering_methods(mat) ## ---- fig.width = 18, fig.height = 14, dev = "jpeg"--------------------------- compare_clustering_methods(mat, plot_type = "heatmap") ## ---- eval = FALSE------------------------------------------------------------ # set.seed(123) # compare_clustering_methods(mat) # set.seed(123) # compare_clustering_methods(mat, plot_type = "heatmap") ## ---- eval = FALSE------------------------------------------------------------ # clt = cmp_make_clusters(mat) # just a list of cluster labels # cmp_make_plot(mat, clt) # cmp_make_plot(mat, clt, plot_type = "heatmap") ## ---- eval = FALSE------------------------------------------------------------ # register_clustering_methods( # method1 = function(mat, ...) ..., # method2 = function(mat, ...) ..., # ... # ) ## ---- fig.width=10, fig.height = 7-------------------------------------------- # perform functional enrichment on the signatures genes from cola anlaysis library(cola) data(golub_cola) res = golub_cola["ATC:skmeans"] library(hu6800.db) x = hu6800ENTREZID mapped_probes = mappedkeys(x) id_mapping = unlist(as.list(x[mapped_probes])) lt = functional_enrichment(res, k = 3, id_mapping = id_mapping) names(lt) head(lt[[1]][, 1:7]) ## ---- fig.width=10, fig.height = 7, out.width = "100%"------------------------ simplifyGOFromMultipleLists(lt, padj_cutoff = 0.001) ## ---- eval = FALSE------------------------------------------------------------ # lt2 = lapply(lt, function(x) structure(x$p.adjust, names = x$ID)) # simplifyGOFromMultipleLists(lt2, padj_cutoff = 0.001) ## ---- eval = FALSE------------------------------------------------------------ # lt3 = lapply(lt, function(x) x$ID[x$p.adjust < 0.001]) # simplifyGOFromMultipleLists(lt3) ## ----------------------------------------------------------------------------- sessionInfo()