## ----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---------------------------------------------------------- library(networkD3) SpidermiRvisualize_mirnanet(data=mir_pharmnet[sample(nrow(mir_pharmnet), 100), ] ) ## ---- eval = TRUE---------------------------------------------------------- biomark_of_interest<-c("hsa-let-7b","MUC1","PEX7","hsa-miR-222") SpidermiRvisualize_BI(data=mir_pharmnet[sample(nrow(mir_pharmnet), 100), ],BI=biomark_of_interest) ## ---- eval = TRUE---------------------------------------------------------- library(visNetwork) SpidermiRvisualize_direction(data=mir_pharmnet[sample(nrow(mir_pharmnet), 100), ] ) ## ---- eval = TRUE---------------------------------------------------------- SpidermiRvisualize_plot_target(data=miRNA_NET[1:15,]) ## ----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 = TRUE,echo = FALSE--------------------------------------------- B<-matrix( c("Gene network", "Validated miRNA-target","","", "Predicted miRNA-target","","","", "Extracellular Circulating microRNAs", "miRNA-disease", "Drug Associations", "GeneMania", "miRTAR", "miRwalk","miRTarBase", "DIANA", "Miranda", "PicTar","TargetScan","miRandola","miR2disease","Pharmaco-miR", "Current","N/A","miRwalk2","miRTarBase 7","DIANA- 5.0","N/A","N/A","TargetScan7.1","miRandola v 02/2017","N/A","N/A", 2016,2009,2015,2017,2013,2010,"N/A","2016",2017,2009,"N/A", "http://genemania.org/data/current/","http://watson.compbio.iupui.edu:8080/miR2Disease/download/miRtar.txt","http://zmf.umm.uni-heidelberg.de/apps/zmf/mirwalk2/downloads/vtm/hsa-vtm-gene.rdata.zip","mirtarbase.mbc.nctu.edu.tw/cache/download/7.0/miRTarBase_SE_WR.xls","https://bioconductor.org/packages/release/bioc/html/miRNAtap.html","https://bioconductor.org/packages/release/bioc/html/miRNAtap.html","https://bioconductor.org/packages/release/bioc/html/miRNAtap.html","https://bioconductor.org/packages/release/bioc/html/miRNAtap.html","http://mirandola.iit.cnr.it/download/miRandola_version_02_2017.txt","http://watson.compbio.iupui.edu:8080/miR2Disease/download/AllEntries.txt","http://pharmaco-mir.org/home/download_VERSE_db/pharmacomir_VERSE_DB.csv" ), nrow=11, ncol=5) colnames(B)<-c("CATEGORY","EXTERNAL DATABASE","VERSION","LAST UPDATE","LINK") ## ---- eval = TRUE, echo = FALSE-------------------------------------------- knitr::kable(B, digits = 2, caption = "Features",row.names = FALSE) ## ---- eval = FALSE--------------------------------------------------------- # # a<-Case_Study1_loading_1_network(species) # b<-Case_Study1_loading_2_network(data=a) # c<-Case_Study1_loading_3_network(data=b,dataFilt=dataFilt,dataClin=dataClin) # d<-Case_Study1_loading_4_network(TERZA_NET=c) # ## ---- eval = FALSE--------------------------------------------------------- # a2<-Case_Study2_loading_1_network(species) # b2<-Case_Study2_loading_2_network(data=a2) # c2<-Case_Study2_loading_3_network(sdas=a2,miRNA_NET=b2) ## ----sessionInfo----------------------------------------------------------- sessionInfo()