## ---- eval = FALSE------------------------------------------------------- # source("https://bioconductor.org/biocLite.R") # biocLite("SpidermiR") ## ---- echo=TRUE, eval = TRUE--------------------------------------------- require(SpidermiR) org<-SpidermiRquery_species(species) ## ---- eval = TRUE, echo = TRUE------------------------------------------- knitr::kable(org, digits = 2, caption = "List of species",row.names = TRUE) ## ---- eval = TRUE-------------------------------------------------------- net_type<-SpidermiRquery_networks_type(organismID=org[9,]) ## ---- eval = TRUE, echo = TRUE------------------------------------------- net_type ## ---- eval = TRUE-------------------------------------------------------- net_shar_prot<-SpidermiRquery_spec_networks(organismID = org[9,], network = "SHpd") ## ---- eval = TRUE, echo = TRUE------------------------------------------- net_shar_prot ## ---- eval = FALSE------------------------------------------------------- # disease<-SpidermiRquery_disease(diseaseID) ## ---- eval = TRUE-------------------------------------------------------- out_net<-SpidermiRdownload_net(net_shar_prot) ## ---- eval = FALSE------------------------------------------------------- # mirna<-c('hsa-miR-567','hsa-miR-566') # SpidermiRdownload_miRNAprediction(mirna_list=mirna) ## ---- eval = FALSE------------------------------------------------------- # list<-SpidermiRdownload_miRNAvalidate(validated) ## ---- eval = TRUE-------------------------------------------------------- mir_pharmaco<-SpidermiRdownload_pharmacomir(pharmacomir=pharmacomir) ## ---- eval = TRUE-------------------------------------------------------- geneSymb_net<-SpidermiRprepare_NET(organismID = org[9,], data = out_net) ## ---- eval = TRUE-------------------------------------------------------- miRNA_NET<-SpidermiRanalyze_mirna_network(data=geneSymb_net,disease="prostate cancer", miR_trg="val") ## ---- eval = FALSE------------------------------------------------------- # miRNA_complNET<-SpidermiRanalyze_mirna_gene_complnet(data=geneSymb_net,disease="prostate cancer", # miR_trg="val") ## ---- eval = TRUE-------------------------------------------------------- mir_pharmnet<-SpidermiRanalyze_mirnanet_pharm(mir_ph=mir_pharmaco,net=miRNA_NET) ## ---- eval = FALSE------------------------------------------------------- # miRNA_NET_ext_circmT<-SpidermiRanalyze_mirna_extra_cir(data=miRNA_complNET,"mT") ## ---- eval = FALSE------------------------------------------------------- # miRNA_NET_ext_circmCT<-SpidermiRanalyze_mirna_extra_cir(data=miRNA_complNET,"mCT") ## ---- eval = FALSE------------------------------------------------------- # biomark_of_interest<-c("hsa-miR-214","PTEN","FOXO1","hsa-miR-27a") # # GIdirect_net<-SpidermiRanalyze_direct_net(data=miRNA_NET,BI=biomark_of_interest) ## ---- eval = FALSE, echo = FALSE----------------------------------------- # str(GIdirect_net) ## ---- eval = FALSE------------------------------------------------------- # # subnet<-SpidermiRanalyze_direct_subnetwork(data=miRNA_NET,BI=biomark_of_interest) # ## ---- eval = FALSE------------------------------------------------------- # # GIdirect_net_neigh<-SpidermiRanalyze_subnetwork_neigh(data=miRNA_NET,BI=biomark_of_interest) ## ---- eval = FALSE------------------------------------------------------- # top10_cent_gene<-SpidermiRanalyze_degree_centrality(miRNA_NET,cut=10) ## ---- eval = FALSE------------------------------------------------------- # comm<- SpidermiRanalyze_Community_detection(data=miRNA_NET,type="FC") ## ---- eval = FALSE------------------------------------------------------- # cd_net<-SpidermiRanalyze_Community_detection_net(data=miRNA_NET,comm_det=comm,size=1) ## ---- eval = FALSE------------------------------------------------------- # gi=c("CF","ROCK1","KIT","CCND2") # mol<-SpidermiRanalyze_Community_detection_bi(data=comm,BI=gi) ## ---- eval = FALSE------------------------------------------------------- # library(networkD3) # # SpidermiRvisualize_mirnanet(data=mir_pharmnet[sample(nrow(mir_pharmnet), 150), ] ) ## ---- eval = FALSE------------------------------------------------------- # # biomark_of_interest<-c("hsa-let-7b","MUC1","PEX7","hsa-miR-222") # SpidermiRvisualize_BI(data=miRNA_NET,BI=biomark_of_interest) ## ---- eval = TRUE-------------------------------------------------------- SpidermiRvisualize_plot_target(data=miRNA_NET) ## ---- eval = TRUE-------------------------------------------------------- SpidermiRvisualize_degree_dist(data=miRNA_NET) ## ---- fig.width=10, fig.height=10,eval = TRUE---------------------------- SpidermiRvisualize_adj_matrix(data=miRNA_NET[1:30,]) ## ----fig.width=4, fig.height=4, eval = TRUE------------------------------ SpidermiRvisualize_3Dbarplot(Edges_1net=1041003,Edges_2net=100016,Edges_3net=3008,Edges_4net=1493,Edges_5net=1598,NODES_1net=16502,NODES_2net=13338,NODES_3net=1429,NODES_4net=675,NODES_5net=712,nmiRNAs_1net=0,nmiRNAs_2net=74,nmiRNAs_3net=0,nmiRNAs_4net=0,nmiRNAs_5net=37) ## ---- eval = FALSE------------------------------------------------------- # # org<-SpidermiRquery_species(species) # net_shar_prot<-SpidermiRquery_spec_networks(organismID = org[6,],network = "SHpd") # out_net<-SpidermiRdownload_net(net_shar_prot) # geneSymb_net<-SpidermiRprepare_NET(organismID = org[6,],data = out_net) # miRNA_complNET<-SpidermiRanalyze_mirna_gene_complnet(data=geneSymb_net, # disease="prostate cancer") # # biomark_of_interest<-read.delim("C:/Users/UserInLab05/Google Drive/MIRNA AND GENEMANIA/ # 1 case study/deg_prostate.txt",header=FALSE) # subnet<-SpidermiRanalyze_direct_subnetwork(data=miRNA_complNET,BI=biomark_of_interest$V1) # comm2<- SpidermiRanalyze_Community_detection(data=subnet,type="FC") # cd_net<-SpidermiRanalyze_Community_detection_net(data=subnet,comm_det=comm2,size=2) # SpidermiRvisualize_mirnanet(data=cd_net) # miRNA_NET<-SpidermiRanalyze_mirna_network(data=geneSymb_net,disease="prostate cancer") # # cd_net_miRNA<-SpidermiRanalyze_Community_detection_net(data=miRNA_NET,comm_det=comm2,size=2) # # SpidermiRvisualize_mirnanet(data=cd_net_miRNA) # # # ## ---- eval = FALSE------------------------------------------------------- # org<-SpidermiRquery_species(species) # net_PHint<-SpidermiRquery_spec_networks(organismID = org[6,],network = "PHint") # out_net<-SpidermiRdownload_net(net_PHint) # geneSymb_net<-SpidermiRprepare_NET(organismID = org[6,],data = out_net) # ds<-do.call("rbind", geneSymb_net) # data1<-as.data.frame(ds[!duplicated(ds), ]) # # sdas<-cbind(data1$gene_symbolA,data1$gene_symbolB) # # miRNA_NET<-SpidermiRanalyze_mirna_network(data=geneSymb_net,disease="breast cancer") # topwhol<-SpidermiRanalyze_degree_centrality(sdas) # top10_cent_gene<-SpidermiRanalyze_degree_centrality(miRNA_NET) # miRNA_degree<-top10_cent_gene[grep("hsa",top10_cent_gene$dfer),] # #