## ---- warning=FALSE, message=FALSE, results='hide'------------------------- library(FELLA) library(igraph) library(magrittr) set.seed(1) # Filter the dre01100 overview pathway, as in the article graph <- buildGraphFromKEGGREST( organism = "dre", filter.path = c("01100")) tmpdir <- paste0(tempdir(), "/my_database") # Make sure the database does not exist from a former vignette build # Otherwise the vignette will rise an error # because FELLA will not overwrite an existing database unlink(tmpdir, recursive = TRUE) buildDataFromGraph( keggdata.graph = graph, databaseDir = tmpdir, internalDir = FALSE, matrices = "none", normality = "diffusion", niter = 100) ## ---- warning=FALSE, message=FALSE, results='hide'------------------------- fella.data <- loadKEGGdata( databaseDir = tmpdir, internalDir = FALSE, loadMatrix = "none" ) ## -------------------------------------------------------------------------- fella.data ## -------------------------------------------------------------------------- cpd.liver <- c( "C12623", "C01179", "C05350", "C05598", "C01586" ) analysis.liver <- enrich( compounds = cpd.liver, data = fella.data, method = "diffusion", approx = "normality") ## -------------------------------------------------------------------------- analysis.liver %>% getInput %>% getName(data = fella.data) ## ---- fig.width=8, fig.height=8-------------------------------------------- plot( analysis.liver, method = "diffusion", data = fella.data, nlimit = 250, plotLegend = FALSE) ## -------------------------------------------------------------------------- g.liver <- generateResultsGraph( object = analysis.liver, data = fella.data, method = "diffusion") tab.liver <- generateResultsTable( object = analysis.liver, data = fella.data, method = "diffusion") ## -------------------------------------------------------------------------- g.liver ## -------------------------------------------------------------------------- path.fig2 <- "dre00360" # Phenylalanine metabolism path.fig2 %in% V(g.liver)$name ## -------------------------------------------------------------------------- tab.liver[tab.liver$Entry.type == "pathway", ] ## -------------------------------------------------------------------------- cpd.liver %in% V(g.liver)$name ## -------------------------------------------------------------------------- cpd.fig2 <- c( "C00079", # Phenylalanine "C00082" # Tyrosine ) cpd.fig2 %in% V(g.liver)$name ## -------------------------------------------------------------------------- cpd.plasma <- c( "C16323", "C00740", "C08323", "C00623", "C00093", "C06429", "C16533", "C00740", "C06426", "C06427", "C07289", "C01879" ) %>% unique analysis.plasma <- enrich( compounds = cpd.plasma, data = fella.data, method = "diffusion", approx = "normality") ## -------------------------------------------------------------------------- analysis.plasma %>% getInput %>% getName(data = fella.data) ## ---- fig.width=8, fig.height=8-------------------------------------------- plot( analysis.plasma, method = "diffusion", data = fella.data, nlimit = 250, plotLegend = FALSE) ## -------------------------------------------------------------------------- g.plasma <- generateResultsGraph( object = analysis.plasma, data = fella.data, method = "diffusion") tab.plasma <- generateResultsTable( object = analysis.plasma, data = fella.data, method = "diffusion") ## -------------------------------------------------------------------------- g.plasma ## -------------------------------------------------------------------------- tab.plasma[tab.plasma$Entry.type == "pathway", ] ## -------------------------------------------------------------------------- path.fig3 <- c( "dre00591", # Linoleic acid metabolism "dre01040", # Biosynthesis of unsaturated fatty acids "dre00592", # alpha-Linolenic acid metabolism "dre00564", # Glycerophospholipid metabolism "dre00480", # Glutathione metabolism "dre00260" # Glycine, serine and threonine metabolism ) path.fig3 %in% V(g.plasma)$name ## -------------------------------------------------------------------------- cpd.plasma %in% V(g.plasma)$name ## -------------------------------------------------------------------------- cpd.fig3 <- c( "C01595", # Linoleic acid "C00157", # Phosphatidylcholine "C00037" # Glycine ) cpd.fig3 %in% V(g.plasma)$name ## -------------------------------------------------------------------------- sessionInfo() ## -------------------------------------------------------------------------- cat(getInfo(fella.data)) ## -------------------------------------------------------------------------- date() ## -------------------------------------------------------------------------- tempfile(pattern = "vignette_dre_", fileext = ".RData") %T>% message("Saving workspace to ", .) %>% save.image(compress = "xz")