# #——回声= FALSE,警告= FALSE,消息= FALSE --------------------------------- devtools: load_all ('.') ## ---- 警告= FALSE,消息= FALSE --------------------------------------------- 图书馆(“yeastExpData ') ## ---- 回声= TRUE ---------------------------------------------------------------- 数据(ccyclered)头(ccyclered ) ## ----------------------------------------------------------------------------- 集群< - ccyclered集群# # #美元从基因名称转换为酿酒基因组数据库的新标准(SGD)基因ids ccyclered SGDID < -子(^年代’,‘S00’,ccyclered SGDID美元)名称(集群)< - ccyclered SGDID美元str(集群 ) ## ---- fig.show =“持有”,回声= TRUE ---------------------------------------------- 数据(Yeast.GO.assocs);str (Yeast.GO.assocs);头(Yeast.GO.assocs);validate_association (Yeast.GO.assocs ) ## ---- eval = FALSE,回声= TRUE --------------------------------------------------- # 库(biomaRt) # rn < - useDataset(“rnorvegicus_gene_ensembl集市= useMart(“运用”))# rgd。symbol=c("As3mt"， "Borcs7"， "Cyp17a1"， "Wbp1l"， "Sfxn2"， "Arl3")attr <- getBM(attributes=c('rgd_symbol'，'go_id')， filters='rgd_symbol'， values=rgd. attr <- getBM(attributes=c('rgd_symbol'，'go_id')，象征,集市rn = ) ## ---- fig.width = 6, fig.height = 4 ----------------------------------------------- entities_attribute_stats (Yeast.GO.assocs) # # #显示Yeast.GO.assocs每个属性的实体的数量分布。con1 <- consolidate_entity_attribute(实体。attribute =酵母. go .assoc, min.entities.per.attr =3 ###只保留与3个或更多实体相关的属性。正= FALSE)暗(Yeast.GO.assocs)暗(Yeast.GO.assocs.cons1) # # #显示数量的减少关联# #——fig.width = 6, fig.height = 4 ----------------------------------------------- 数据(mi.GO.Yeast) Yeast.GO.assocs.cons < consolidate_entity_attribute(实体。attribute =酵母. go .assoc, min.entities.per.attr =3, mutt .inf=mi.GO。酵母###使用预先计算的互信息，U.limit = c(0.1, 0.001) ###计算这些不确定性水平的综合关联###显示不确定性str(酵母. go .assocs.cons) ## ----------------------------------------------------------------------------- data(酵母. go .assocs) ###因为它需要时间， we use a small sampled subset of associations entity.attribute.sampled <- Yeast.GO.assocs[sample(1:nrow(Yeast.GO.assocs),100),] mi.GO.Yeast.sampled <- attribute_mut_inf( entity.attribute = entity.attribute.sampled , show.progress = FALSE ## for this small example do not print progress ) str(mi.GO.Yeast.sampled) ## ---- fig.width=6, fig.height=4----------------------------------------------- mi.by.swaps<-clusterJudge( clusters = clusters , entity.attribute=Yeast.GO.assocs.cons[["0.001"]] , plot.notes='Yeast clusters judged at uncertainty level 0.001 - Ref: Tavazoie S,& all `Systematic determination of genetic network architecture. Nat Genet. 1999`' , plot.saveRDS.file= 'cj.rds') ### save the plot for later use p <- readRDS('cj.rds') ### retrieve the previous plot pdf('cj.pdf'); plot(p); dev.off() ### plot on another device