## ----setup, echo=FALSE-------------------------------------------------------- knitr::opts_chunk$set(message=FALSE, fig.path='figures/') ## ---- message = FALSE, tidy = TRUE-------------------------------------------- ## Load MetaboSignal library(MetaboSignal) ## ---- tidy = TRUE------------------------------------------------------------- ## Regulatory interactions data("regulatory_interactions") head(regulatory_interactions[, c(1,3,5)]) ## KEGG metabolic pathways data("kegg_pathways") head(kegg_pathways[, -2]) ## KEGG signaling pathways tail(kegg_pathways[, -2]) ## ---- tidy = TRUE, eval=FALSE------------------------------------------------- # ## Get IDs of metabolic and signaling human pathways # hsa_paths <- MS_getPathIds(organism_code = "hsa") ## ---- tidy = TRUE, tidy.opts=list(indent = 4, width.cutoff = 50)-------------- ## Create metabo_paths and signaling_paths vectors metabo_paths <- kegg_pathways[kegg_pathways[, "Path_type"] == "metabolic", "Path_id"] signaling_paths <- kegg_pathways[kegg_pathways[, "Path_type"] == "signaling", "Path_id"] ## ----tidy = TRUE, tidy.opts=list(indent = 4, width.cutoff = 50), results='asis', eval=FALSE---- # ## Build KEGG network (might take a while) # keggNet_example <- MS_keggNetwork(metabo_paths, signaling_paths, expand_genes = TRUE, # convert_entrez = TRUE) ## ---- tidy = TRUE------------------------------------------------------------- ## See network format head(keggNet_example) ## ---- tidy = TRUE, tidy.opts=list(indent = 4, width.cutoff = 55)-------------- ## Get all types of interaction all_types <- unique(unlist(strsplit(keggNet_example[, "interaction_type"], "/"))) all_types <- gsub("k_", "", all_types) ## Select wanted interactions wanted_types <- setdiff(all_types, c("unknown", "indirect-compound", "indirect-effect", "dissociation", "state-change", "binding", "association")) print(wanted_types) # interactions that will be retained ## Filter keggNet_example to retain only wanted interactions wanted_types <- paste(wanted_types, collapse = "|") keggNet_clean <- keggNet_example[grep(wanted_types, keggNet_example[, 3]), ] ## ---- tidy = TRUE------------------------------------------------------------- ## Build regulatory network of TRRUST interactions trrustNet_example <- MS2_ppiNetwork(datasets = "trrust") ## Build regulatory network of OmniPath interactions omnipathNet_example <- MS2_ppiNetwork(datasets = "omnipath") ## Build regulatory network by merging OmniPath and TRRUST interactions ppiNet_example <- MS2_ppiNetwork(datasets = "all") ## See network format head(ppiNet_example) ## ----tidy = TRUE, tidy.opts=list(indent = 4, width.cutoff = 60), results='asis', eval=FALSE---- # ## Merge networks # mergedNet_example <- MS2_mergeNetworks(keggNet_clean, ppiNet_example) ## ---- message = FALSE, tidy = TRUE-------------------------------------------- ## See network format head(mergedNet_example)