### R code from vignette source 'usingpcxnData.Rnw' ################################################### ### code chunk number 1: usingpcxnData.Rnw:35-77 ################################################### # Use the pcxn library library(pcxn) library(pcxnData) # Load the data ds = c("cp_gs_v5.1", "gobp_gs_v5.1", "h_gs_v5.1","pathprint.Hs.gs", "pathCor_CPv5.1_dframe","pathCor_GOBPv5.1_dframe","pathCor_Hv5.1_dframe", "pathCor_pathprint_v1.2.3_dframe","pathCor_CPv5.1_unadjusted_dframe", "pathCor_GOBPv5.1_unadjusted_dframe","pathCor_Hv5.1_unadjusted_dframe", "pathCor_pathprint_v1.2.3_unadjusted_dframe") data(list = ds) # Explore the static extendable network by focusing on single pathways and their # 10 most correlated neighbours in the pathprint collection pcxn.obj <- pcxn_explore(collection = "pathprint", query_geneset = "Alzheimer's disease (KEGG)", adj_overlap = FALSE, top = 10, min_abs_corr = 0.05, max_pval = 0.05) # Analyse relationships between groups of pathways shown to be enriched in the # collection by gene set enrichment pcxn.obj <- pcxn_analyze(collection = "pathprint", phenotype_0_genesets = c("ABC transporters (KEGG)", "ACE Inhibitor Pathway (Wikipathways)", "AR down reg. targets (Netpath)"), phenotype_1_genesets = c("DNA Repair (Reactome)"), adj_overlap = FALSE, top = 10, min_abs_corr = 0.05, max_pval = 0.05 ) # Generate the heatmap for any pcxn object generated by the # explore or analyze function hm <- pcxn_heatmap(pcxn.obj , cluster_method = "complete") # Get the gene members (Entrez Ids and symbols) of any pathway/geneset in the # data gene_members <- pcxn_gene_members(pathway_name = "Alzheimer's disease (KEGG)")