gs_dendro {GeneTonic} | R Documentation |
Calculate (and plot) the dendrogram of the gene set enrichment results
gs_dendro( res_enrich, gtl = NULL, n_gs = nrow(res_enrich), gs_ids = NULL, gs_dist_type = "kappa", clust_method = "ward.D2", color_leaves_by = "z_score", size_leaves_by = "gs_pvalue", color_branches_by = "clusters", create_plot = TRUE )
res_enrich |
A |
gtl |
A |
n_gs |
Integer value, corresponding to the maximal number of gene sets to
be included (from the top ranked ones). Defaults to the number of rows of
|
gs_ids |
Character vector, containing a subset of |
gs_dist_type |
Character string, specifying which type of similarity (and
therefore distance measure) will be used. Defaults to |
clust_method |
Character string defining the agglomeration method to be
used for the hierarchical clustering. See |
color_leaves_by |
Character string, which columns of |
size_leaves_by |
Character string, which columns of |
color_branches_by |
Character string, which columns of |
create_plot |
Logical, whether to create the plot as well. |
A dendrogram object is returned invisibly, and a plot can be generated as well on that object.
library("macrophage") library("DESeq2") library("org.Hs.eg.db") library("AnnotationDbi") # dds object data("gse", package = "macrophage") dds_macrophage <- DESeqDataSet(gse, design = ~ line + condition) rownames(dds_macrophage) <- substr(rownames(dds_macrophage), 1, 15) dds_macrophage <- estimateSizeFactors(dds_macrophage) # annotation object anno_df <- data.frame( gene_id = rownames(dds_macrophage), gene_name = mapIds(org.Hs.eg.db, keys = rownames(dds_macrophage), column = "SYMBOL", keytype = "ENSEMBL" ), stringsAsFactors = FALSE, row.names = rownames(dds_macrophage) ) # res object data(res_de_macrophage, package = "GeneTonic") res_de <- res_macrophage_IFNg_vs_naive # res_enrich object data(res_enrich_macrophage, package = "GeneTonic") res_enrich <- shake_topGOtableResult(topgoDE_macrophage_IFNg_vs_naive) res_enrich <- get_aggrscores(res_enrich, res_de, anno_df) gs_dendro(res_enrich, n_gs = 100 )