## ----设置，echo = false -------------------------------------------------------------------------------------------------------------------------------------------------- knitr::opts_chunk$set(message=FALSE, fig.path='figures/') ## ---- message = FALSE, tidy = TRUE-------------------------------------------- ## Load MetaboSignal library(代谢信号）## ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ##监管互动数据（“ congulatory_interactions”）头（consulatory_interactions [，C（1,3,5）]）## kegg代谢路径数据（“ kegg_pathways”）头（kegg_pathways [，-2]）## kegg信号通路尾巴（kegg_pathways [， - 2]）## ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ##获取代谢的ID和信号人类路径＃hsa_paths <-ms_getPathIds（有机机_code =“ hsa”）## ---------------------------------------------------------------------------------------------------------------------------------------------------- ##创建metabo_path和signding_paths vectors metabo_paths <-kegg_pathways [kegg_pathways [，“ path_type”] ==“代谢”，“ path_id”] signal_id'] signal_id_paths <-kegg_pathways [kegg_pathways [，“ path_type”] ==“信号”，“ path_id”] ## ---- tidy = true，tidy.opts = list = 4，width.cutoff = 50），结果='asis ='asis'，eval = false ----＃##构建kegg网络（可能需要一段时间）＃keggnet_example <-ms_keggnetwork（metabo_paths，signding_paths，explient_genes = true，true，＃convert_entrez = true）## ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ##请参阅网络格式头（keggnet_example）## -------------------------------------------------------------------------------- ##获取所有类型的交互作用all_types < - unique（unlist（strsplit（keggnet_example [，“ interaction_type”]，“/”）））all_types <-gsub（“ k_”，“”，“”，all_types）##选择通缉互动white_types <-setDiff（all_types，c（“ unknown”，“ indirect-compound”，“ indirect-effect”，“ natirect-effect”，“ ofcociation”，“ ofcociation”，“ state-change”，“ state-change”，“ nate-change”，“ binding”，“ binding”，“ binding”，“ cociedial''，“关联”，“协会”）print（wenth_types）＃将保留## filter keggnet_example的互动以保留所需的互动washing_types <-aste（paste）（athen_types，collapse =“ |”）keggnet_clean <-keggnet_example [grep（athen_types，keggnet_example [，3]），] ## - ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ ##建立监管网络 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)