## ----setup, include=FALSE------------------------------------------------ knitr::opts_chunk$set(dpi = 300) knitr::opts_chunk$set(cache=FALSE) ## ---- eval = TRUE, echo = FALSE,hide=TRUE, message=FALSE,warning=FALSE---- devtools::load_all() ## ---- eval = FALSE------------------------------------------------------- ## source("https://bioconductor.org/biocLite.R") ## biocLite("SpidermiR") ## ---- eval = TRUE-------------------------------------------------------- org<-SpidermiRquery_species(species) ## ---- eval = TRUE, echo = FALSE------------------------------------------ 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 = FALSE------------------------------------------ net_type ## ---- eval = TRUE-------------------------------------------------------- net_shar_prot<-SpidermiRquery_spec_networks(organismID = org[9,], network = "SHpd") ## ---- eval = TRUE, echo = FALSE------------------------------------------ net_shar_prot ## ---- eval = TRUE-------------------------------------------------------- disease<-SpidermiRquery_disease(diseaseID) ## ---- eval = TRUE, echo = FALSE------------------------------------------ disease ## ---- eval = TRUE-------------------------------------------------------- out_net<-SpidermiRdownload_net(net_shar_prot) ## ---- eval = TRUE, echo = FALSE------------------------------------------ str(out_net) ## ---- eval = FALSE------------------------------------------------------- ## mirna<-c('hsa-miR-567','hsa-miR-566') ## SpidermiRdownload_miRNAprediction(mirna_list=mirna) ## ---- eval = FALSE------------------------------------------------------- ## list<-SpidermiRdownload_miRNAvalidate(validated) ## ---- eval = FALSE------------------------------------------------------- ## list<-SpidermiRdownload_miRNAextra_cir(miRNAextra_cir) ## ---- eval = TRUE-------------------------------------------------------- mir_pharmaco<-SpidermiRdownload_pharmacomir(pharmacomir=pharmacomir) ## ---- eval = TRUE-------------------------------------------------------- geneSymb_net<-SpidermiRprepare_NET(organismID = org[9,], data = out_net) ## ---- eval = TRUE, echo = FALSE------------------------------------------ knitr::kable(geneSymb_net[[1]][1:5,c(1,2,3,5,8)], digits = 2, caption = "shared protein domain",row.names = FALSE) ## ---- eval = TRUE-------------------------------------------------------- miRNA_NET<-SpidermiRanalyze_mirna_network(data=geneSymb_net,disease="prostate cancer",miR_trg="val") ## ---- eval = TRUE, echo = FALSE------------------------------------------ str(miRNA_NET) ## ---- 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 = TRUE-------------------------------------------------------- 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 = TRUE, 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 = TRUE-------------------------------------------------------- miRNA_cN <-data.frame(gA=c('IGFL3','GABRA1'),gB=c('IGFL2','KRT13'),stringsAsFactors=FALSE) tumour<-c("TCGA-E9-A1RD-11A","TCGA-E9-A1RC-01A") normal<-c("TCGA-BH-A18P-11A","TCGA-BH-A18L-11A") de_int<-SpidermiRanalyze_DEnetworkTCGA(data=miRNA_cN, TCGAmatrix=Data_CANCER_normUQ_filt, tumour, normal ) ## ---- eval = TRUE-------------------------------------------------------- library(networkD3) SpidermiRvisualize_mirnanet(data=mir_pharmnet[sample(nrow(mir_pharmnet), 150), ] ) ## ---- eval = TRUE-------------------------------------------------------- biomark_of_interest<-c("hsa-let-7b","MUC1","PEX7","hsa-miR-222") SpidermiRvisualize_BI(data=mir_pharmnet[sample(nrow(mir_pharmnet), 150), ] ,BI=biomark_of_interest) ## ---- eval = TRUE-------------------------------------------------------- library(visNetwork) SpidermiRvisualize_direction(data=mir_pharmnet[sample(nrow(mir_pharmnet), 30), ] ) ## ---- eval = TRUE-------------------------------------------------------- SpidermiRvisualize_plot_target(data=miRNA_NET) ## ----fig.width=4, fig.height=4, 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",miR_trg="val") ## ## 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$gene_symbolB) ## sdas<-as.data.frame(sdas[!duplicated(sdas), ]) ## miRNA_NET<-SpidermiRanalyze_mirna_network(data=geneSymb_net,disease="breast cancer") ## topwhol<-SpidermiRanalyze_degree_centrality(sdas) ## top10_cent_gene<-SpidermiRanalyze_degree_centrality(miRNA_NET) ## miRNA_degree<-top10_cent_gene[grep("hsa",top10_cent_gene$dfer),] ## ## ## ----sessionInfo--------------------------------------------------------- sessionInfo()