## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, fig.align= "center", comment = "#>" ) ## ----Bioconductor installation, echo=TRUE, eval=FALSE------------------------- # if (!requireNamespace("BiocManager", quietly = TRUE)) # install.packages("BiocManager") # BiocManager::install('GmicR') ## ----downloading data, echo=TRUE---------------------------------------------- url <- "http://xcell.ucsf.edu/iris_u133a_expr.txt" dat_download <- data.frame(read.delim(url), row.names = 1, stringsAsFactors = FALSE, check.rows = FALSE) # data are transposed for processing datExpr0<-data.frame(t(dat_download)) ## ----checking genes, message=FALSE, warning=FALSE----------------------------- library(WGCNA) gsg = goodSamplesGenes(datExpr0, verbose = 3) # columns must be genes gsg$allOK ## ----checking samples--------------------------------------------------------- sampleTree = hclust(dist(datExpr0), method = "average"); par(cex = 0.6); par(mar = c(0,4,2,0)) plot(sampleTree, main = "Sample Filtering", labels = FALSE) # final expression set ---------------------------------------------------- datExpr = datExpr0 ## ----saving expression data, echo=TRUE, eval = FALSE-------------------------- # Exps_for_xCell_analysis<-data.frame(t(datExpr), check.names = FALSE) # # write.csv(Exps_for_xCell_analysis, file = "Exps_for_xCell_analysis.csv") ## ----xCell email screen shot, echo=FALSE, out.width = '80%'------------------- xCell_email_dir<-system.file("extdata", "xCell_email.png", package = "GmicR", mustWork = TRUE) knitr::include_graphics(xCell_email_dir) ## ----clearing environment and loading data, include=FALSE--------------------- remove(list = ls()) library(GmicR) sample_dat_dir<-system.file("extdata", "sample_dat.Rdata", package = "GmicR", mustWork = TRUE) load(sample_dat_dir) ## ----module detection, echo=TRUE, results=FALSE------------------------------- library(GmicR) GMIC_Builder<-Auto_WGCNA(sample_dat, mergeCutHeight = 0.35, minModuleSize = 10, deepSplit = 4, networkType = "signed hybrid", TOMType = "unsigned", corFnc = "bicor", sft_RsquaredCut = 0.85, reassignThreshold = 1e-06, maxBlockSize = 25000) ## ----modules, echo=TRUE, fig.height=5, fig.width=5---------------------------- GMIC_Builder$Input_Parameters ## ----plot1,, echo=TRUE, fig.height=5, fig.width=5----------------------------- GMIC_Builder$Output_plots$soft_threshold_plot ## ----loading processed data, include=FALSE------------------------------------ GMIC_Builder_dir<-system.file("extdata", "GMIC_Builder.Rdata", package = "GmicR", mustWork = TRUE) load(GMIC_Builder_dir) ## ----plot2, , echo=TRUE, fig.height=5, fig.width=5---------------------------- GMIC_Builder$Output_plots$module_clustering ## ----plot3, , echo=TRUE, fig.height=5, fig.width=5---------------------------- GMIC_Builder$Output_plots$net_dendrogram ## ----GO module annotations, echo=TRUE----------------------------------------- # Module hubs and Gene influence GMIC_Builder<-Query_Prep(GMIC_Builder, calculate_intramodularConnectivity= TRUE, Find_hubs = TRUE) head(GMIC_Builder$Query) ## ----GO enrichment, echo=TRUE------------------------------------------------- GMIC_Builder<-GSEAGO_Builder(GMIC_Builder, species = "Homo sapiens", ontology = "BP", no_cores = 1) ## ----GO module names, echo=TRUE----------------------------------------------- GMIC_Builder<-GO_Module_NameR(GMIC_Builder) ## ----GO_table----------------------------------------------------------------- head(GMIC_Builder$GO_table, n = 4) ## ----GO_Query----------------------------------------------------------------- head(GMIC_Builder$GO_Query, n = 4) ## ----cell signatures, echo=TRUE----------------------------------------------- file_dir<-system.file("extdata", "IRIS_xCell_sig.txt", package = "GmicR", mustWork = TRUE) ## ----discretizing data-------------------------------------------------------- GMIC_Builder_disc<-Data_Prep(GMIC_Builder, xCell_Signatures = file_dir, ibreaks=10, Remove_ME0 = TRUE) head(GMIC_Builder_disc$disc_data[sample(seq(1,64),4)]) ## ----loading processed network, message=FALSE, warning=FALSE, include=FALSE---- GMIC_net_dir<-system.file("extdata", "GMIC_net.Rdata", package = "GmicR", mustWork = TRUE) load(GMIC_net_dir) ## ----bnlearning, eval=FALSE, echo=TRUE---------------------------------------- # # no_cores<-1 # multicore support # cl<-parallel::makeCluster(1) # # # GMIC_net<-bn_tabu_gen(GMIC_Builder_disc, # cluster = cl, debug = FALSE, # bootstraps_replicates = 50, score = "bds") # # parallel::stopCluster(cl) # stop cluster ## ----detecting inverse relationships, echo=TRUE------------------------------- GMIC_Final<-InverseARCs(GMIC_net, threshold = -0.3) ## ----Visualizing network, echo=TRUE------------------------------------------- GMIC_Final_dir<-system.file("extdata", "GMIC_Final.Rdata", package = "GmicR", mustWork = TRUE) load(GMIC_Final_dir) if(interactive()){ Gmic_viz(GMIC_Final) } ## ----screen shot1, echo=FALSE, out.width = '100%'----------------------------- example_shiny_dir<-system.file("extdata", "example_shiny1.png", package = "GmicR", mustWork = TRUE) knitr::include_graphics(example_shiny_dir) ## ----screen shot2, echo=FALSE, out.width = '100%'----------------------------- example_shiny_dir<-system.file("extdata", "example_shiny2.png", package = "GmicR", mustWork = TRUE) knitr::include_graphics(example_shiny_dir) ## ----screen shot3, echo=FALSE, out.width = '100%'----------------------------- example_shiny_dir<-system.file("extdata", "example_shiny3.png", package = "GmicR", mustWork = TRUE) knitr::include_graphics(example_shiny_dir)