# # - - - - -设置,回声= FALSE - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - knitr:: opts_chunk设置美元(消息= FALSE, fig.path =“数据/”)# #——包括= FALSE - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -库(MetaboSignal) # #——消息= FALSE,整洁= TRUE - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - MS_keggFinder (KEGG_database =“有机体”,匹配=鼠属)# #——整洁= TRUE,整洁。选择=列表(缩进= 4、宽度。截止= 50)- - - - - - - - - - - - - - - - - - MS_keggFinder (KEGG_database =“通路”,匹配= c(“醇”、“磷酸肌醇”、“胰岛素信号”,“一种蛋白激酶”),organism_code =“优化”)# #——整洁= TRUE - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - metabo_paths < - c (“rno00010”、“rno00562”) signaling_paths < - c (“rno04910”、“rno04151”) # #——整洁= TRUE,整洁。选择=列表(缩进= 4、宽度。截止= 50),结果=‘黑名单’,eval = FALSE - - - - - # MetaboSignal_table <——MS_keggNetwork (metabo_paths = metabo_paths # signaling_paths = signaling_paths) # # #——整洁= TRUE,整洁。选择=列表(缩进= 4、宽度。截止= 50)- - - - - - - - - - - - - - - - - - MetaboSignal_table <——MS_replaceNode (node1 = c (“cpd: C00267”、“cpd: C00221”), node2 =“cpd: C00031 MetaboSignal_table) # #——整洁= TRUE,整洁。选择=列表(缩进= 4、宽度。截止= 50),消息= FALSE——MS_findMappedNodes(节点= c (“cpd: C00267”、“cpd: C00221”、“cpd: C00031”), MetaboSignal_table) # #——整洁= TRUE,整洁。选择=列表(缩进= 4、宽度。截止= 50),消息= FALSE - - - - - # #得到KEGG IDs MS_convertGene (= c基因(“303565”、“65038”、“309179”),organism_code =“优化”,organism_name =“鼠”,输出=“矩阵”)MS_distances (MetaboSignal_table organism_code =“优化”,source_genes = c (“K01084”、“K15909”,“K11584”), target_metabolites =“cpd: C00031”,名称= TRUE) # #——整洁= TRUE,整洁。选择=列表(缩进= 4、宽度。截止= 50),eval = FALSE - - - - - # MS_shortestPathsNetwork (MetaboSignal_table organism_code =“优化”,# source_nodes = c (“K01084”、“K15909”,“K11584”), # target_nodes =“cpd: C00031”类型=“bw”, # file_name =“女士”)